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  • 1.
    Barrera Diaz, Carlos Alberto
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Fathi, Masood
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment. Division of Industrial Engineering and Management, Uppsala University, Uppsala, Sweden.
    Aslam, Tehseen
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Ng, Amos H. C.
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment. Division of Industrial Engineering and Management, Uppsala University, Uppsala, Sweden.
    Optimizing reconfigurable manufacturing systems: A Simulation-based Multi-objective Optimization approach2021In: Procedia CIRP, ISSN 2212-8271, E-ISSN 2212-8271, Vol. 104, p. 1837-1842Article in journal (Refereed)
    Abstract [en]

    Application of reconfigurable manufacturing systems (RMS) plays a significant role in manufacturing companies’ success in the current fiercely competitive market. Despite the RMS’s advantages, designing these systems to achieve a high-efficiency level is a complex and challenging task that requires the use of optimization techniques. This study proposes a simulation-based optimization approach for optimal allocation of work tasks and resources (i.e., machines) to workstations. Three conflictive objectives, namely maximizing the throughput, minimizing the buffers’ capacity, and minimizing the number of machines, are optimized simultaneously while considering the system’s stochastic behavior to achieve the desired system’s configuration.

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  • 2.
    Beheshtinia, Mohammad Ali
    et al.
    Department of Industrial Engineering, University of Semnan, Iran.
    Ahmadi, Bahar
    Department of Industrial Engineering, University of Semnan, Iran.
    Fathi, Masood
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    A Genetic Algorithm with Multiple Populations to Reduce Fuel Consumption in Supply Chain2021In: International Journal of Transportation Engineering, ISSN 2322-259X, Vol. 8, no 3, p. 225-246Article in journal (Refereed)
    Abstract [en]

    Reducing fuel consumption by transportation fleet in a supply chain, reduces transportation costs and consequently, the product final cost. Moreover, it reduces environmental pollution, and in some cases, it helps governments constitute less subsidies for fuels. In this paper, a supply chain scheduling is studied, with the two objective functions of minimizing the total fuel consumption, and the total order delivery time. After presenting the mathematical model of the problem, a genetic algorithm, named Social Genetic Algorithm (SGA) is proposed to solve it. The proposed algorithm helps decision makers determine the allocation of orders to the suppliers and vehicles and production and transportation scheduling to minimize total order delivery time and fuel consumption. In order for SGA performance evaluation, its results are compared with another genetic algorithm in the literature and optimal solution. Finally, a sensitivity analysis is performed on SGA. The results of comparisons also show the high performance of SGA. Moreover, by increasing the number of suppliers and vehicles and decreasing the number of orders, the value of the objective function is reduced.

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  • 3.
    Beheshtinia, Mohammad Ali
    et al.
    Industrial Engineering Department, Faculty of Engineering, Semnan University, Iran.
    Bahrami, Fatemeh
    Industrial Engineering Department, Faculty of Engineering, Semnan University, Iran.
    Fathi, Masood
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment. Division of Industrial Engineering and Management, Department of Civil and Industrial Engineering, Uppsala University, Sweden.
    Asadi, Shahla
    Department of Information Systems and Business Analytics, Kent State University, OH, USA.
    Evaluating and prioritizing the healthcare waste disposal center locations using a hybrid multi-criteria decision-making method2023In: Scientific Reports, E-ISSN 2045-2322, Vol. 13, no 1, article id 15130Article in journal (Refereed)
    Abstract [en]

    Healthcare waste disposal center location (HCWDCL) impacts the environment and the health of living beings. Different and sometimes contradictory criteria in determining the appropriate site location for disposing of healthcare waste (HCW) complicate the decision-making process. This research presents a hybrid multi-criteria decision-making (MCDM) method, named PROMSIS, to determine the appropriate HCWDCL in a real case. The PROMSIS is the combination of two well-known MCDM methods, namely TOPSIS and PROMETHEE. Moreover, fuzzy theory is used to describe the uncertainties of the problem parameters. To provide a reliable decision on selecting the best HCWDCL, a comprehensive list of criteria is identified through a literature review and experts’ opinions obtained from the case study. In total, 40 criteria are identified and classified into five major criteria, namely economic, environmental, social, technical, and geological. The weight of the considered criteria is determined by the Analytical Hierarchy Process (AHP) method. Then, the score of the alternative HCWDCLs in each considered criterion is obtained. Finally, the candidate locations for disposing of HCWs are ranked by the proposed fuzzy PROMSIS method. The results show that the most important criteria in ranking the alternatives in the studied case are economic, environmental, and social, respectively. Moreover, the sub-criteria of operating cost, transportation cost, and pollution are identified as the most important sub-criteria, respectively.

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  • 4.
    Beheshtinia, Mohammad Ali
    et al.
    Industrial Engineering Department, Faculty of Engineering, Semnan University, Iran.
    Fathi, Masood
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment. Division of Industrial Engineering and Management, Uppsala University, Sweden.
    Energy‐efficient and sustainable supply chain in the manufacturing industry2023In: Energy Science & Engineering, ISSN 2050-0505, Vol. 11, no 1, p. 357-382Article in journal (Refereed)
    Abstract [en]

    This study aims at reducing energy consumption in supply chain networks by providing optimal integrated production and transportation scheduling. The considered supply chain consists of one main manufacturing center, multiple production units (i.e., suppliers), and multiple heterogeneous vehicles as the transportation fleet. To schedule this complex supply chain network in an energy-efficient way, several decisions should be made concerning the assignment of orders to suppliers and determining their production sequence, splitting orders, assigning orders to vehicles, and assigning delivery priority to orders. To cope with the problem, a mixed-integer linear programming model is presented. Due to the complexity of the problem, a novel development of the genetic algorithm named the Multiple Reference Group Genetic Algorithm (MRGGA) is also proposed. Four objectives are considered to be optimized to meet both suitability and energy-efficiency aspects in the supply chain network. These optimization objectives are to minimize the total orders' delivery times to the manufacturing center, fuel consumption by the vehicles, energy consumption at supplies, and maximize orders' quality. To analyze the performance of the proposed algorithm, a real case and a set of generated instances are solved. The results obtained by the proposed algorithm are compared with an existing genetic algorithm in the literature. Moreover, the results are also compared with the optimal solutions obtained from the mathematical model for small-size problems. The results of the comparisons show the efficiency of the proposed MRGGA in finding energy-efficient solutions for the considered supply chain network.

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  • 5.
    Beheshtinia, Mohammad Ali
    et al.
    Industrial Engineering Department, Semnan University, Iran.
    Feizollahy, Parisa
    Industrial Engineering Department, Semnan University, Iran.
    Fathi, Masood
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment. Division of Industrial Engineering and Management, Uppsala University, Sweden.
    Supply Chain Optimization Considering Sustainability Aspects2021In: Sustainability, E-ISSN 2071-1050, Vol. 13, no 21, p. 1-23, article id 11873Article in journal (Refereed)
    Abstract [en]

    Supply chain optimization concerns the improvement of the performance and efficiency of the manufacturing and distribution supply chain by making the best use of resources. In the context of supply chain optimization, scheduling has always been a challenging task for experts, especially when considering a distributed manufacturing system (DMS). The present study aims to tackle the supply chain scheduling problem in a DMS while considering two essential sustainability aspects, namely environmental and economic. The economic aspect is addressed by optimizing the total delivery time of order, transportation cost, and production cost while optimizing environmental pollution and the quality of products contribute to the environmental aspect. To cope with the problem, it is mathematically formulated as a mixed-integer linear programming (MILP) model. Due to the complexity of the problem, an improved genetic algorithm (GA) named GA-TOPKOR is proposed. The algorithm is a combination of GA and TOPKOR, which is one of the multi-criteria decision-making techniques. To assess the efficiency of GA-TOPKOR, it is applied to a real-life case study and a set of test problems. The solutions obtained by the algorithm are compared against the traditional GA and the optimum solutions obtained from the MILP model. The results of comparisons collectively show the efficiency of the GA-TOPKOR. Analysis of results also revealed that using the TOPKOR technique in the selection operator of GA significantly improves its performance.

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  • 6.
    Beheshtinia, Mohammad Ali
    et al.
    Industrial Engineering Department, Faculty of Engineering, Semnan University, Iran.
    Jafari Kahoo, Sanaz
    Industrial Engineering Department, Faculty of Engineering, Semnan University, Iran.
    Fathi, Masood
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment. Division of Industrial Engineering and Management, Department of Civil and Industrial Engineering, Uppsala University, Sweden.
    Prioritizing healthcare waste disposal methods considering environmental health using an enhanced multi-criteria decision-making method2023In: Environmental Pollutants and Bioavailability, ISSN 2639-5932, Vol. 35, no 1, p. 250-269, article id 2218568Article in journal (Refereed)
    Abstract [en]

    The Healthcare Waste Disposal Method Selection (HCWDMS) is a complicated problem due to multiple and often contradictory criteria with different importance degrees. Thus, decision-makers are restored to multi-criteria decision-making (MCDM) methods to prioritize and select the best HCW disposal methods. This study introduces an enhanced MCDM method to deal with the HCWDMS problem. To address the problem, a comprehensive list of criteria and HCW disposal methods are identified. All the criteria are categorized into four main criteria, and Fuzzy Analysis Hierarchy Process is used to determine the weights of considered criteria and sub-criteria. The study results show that environmental, economic, technical, and social criteria are the most important in selecting disposal methods, respectively. Moreover, the sub-criteria of ‘Health Risk’, ‘Release with health effects’, and ‘Capital cost’ have the highest importance, respectively. Additionally, the methods of ‘Microwave’, ‘Sterilization by autoclave’, and ‘Reverse polymerization’ have the highest priority, respectively.

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  • 7.
    Beheshtinia, Mohammad Ali
    et al.
    Department of Industrial Engineering, Semnan University, Iran.
    Jozi, Ali
    Department of Industrial Engineering, Semnan University, Iran.
    Fathi, Masood
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment. Division of Industrial Engineering and Management, Department of Civil and Industrial Engineering, Uppsala University, Sweden.
    Optimizing disaster relief goods distribution and transportation: a mathematical model and metaheuristic algorithms2023In: Applied Mathematics in Science and Engineering, E-ISSN 2769-0911, Vol. 31, no 1, article id 2252980Article in journal (Refereed)
    Abstract [en]

    The effective distribution of relief goods is critical in mitigating the impact of natural disasters and preserving human life. This study addresses a relief goods distribution problem, assuming the existence of multiple relief orders that must be delivered to various disaster-stricken regions from a network of warehouses using a fleet of diverse vehicles. The objective is to identify the most suitable warehouse for each relief order, allocate relief orders to vehicles, batch the orders in the designated vehicles, and devise routing plans to minimize the total delivery time. A mixed-integer linear programming model is formulated to tackle this problem. Owing to the problem’s NP-hard nature, a metaheuristic algorithm, known as the Multiple League Championship Algorithm (MLCA), is developed. Furthermore, two innovative variants of the MLCA , namely the League Base Multiple League Championship Algorithm (L- MLCA) and the Playoff Multiple League Championship Algorithm (P-MLCA), are introduced.Experimental results indicate that the P-MLCA outperforms the other two algorithms. The solutions derived from the P-MLCA are compared with the optimal solutions obtained by a commercial solver for small-scale problems. This comparative analysis demonstrates the promising performance of the P-MLCA in finding the optimal distribution of relief goods.

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  • 8.
    Beheshtinia, Mohammad Ali
    et al.
    Industrial Engineering Department, Faculty of Engineering, Semnan University, Iran.
    Sayadinia, Shakiba
    Industrial Engineering Department, Faculty of Engineering, Semnan University, Iran.
    Fathi, Masood
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment. Division of Industrial Engineering and Management, Department of Civil and Industrial Engineering, Uppsala University, Sweden.
    Identifying and prioritizing marketing strategies for the building energy management systems using a hybrid fuzzy MCDM technique2023In: Energy Science & Engineering, ISSN 2050-0505, Vol. 11, no 11, p. 4324-4348Article in journal (Refereed)
    Abstract [en]

    Preventing energy waste in residential and office buildings has emerged as a critical issue in both developed and developing countries over recent decades. The growing demand for oil and energy reserves has amplified the urgency of this concern. The deployment of building energy management systems (BEMSs) can lead to timely responses to changes in environmental conditions, the prevention of energy wastage, a reduction in CO2 emissions, and an increase in the longevity of building equipment. Despite the undeniable benefits of BEMSs, their market size remains small, creating challenges for providers in reaching potential customers. This research seeks to identify and prioritize the marketing strategies for BEMSs. A case study was conducted, employing the “Strengths, Weaknesses, Opportunities, and Threats” analysis as a tool for identifying marketing strategies related to BEMSs. This method resulted in the identification of 18 distinct marketing strategies. These strategies were subsequently prioritized using a novel fuzzy multicriteria decision-making technique, VIkor-topSIS, considering six specific criteria. The findings of the study suggested a hierarchical influence of six criteria on the BEMS market, arranged in the following order of significance: effectiveness, cost, attainability, complexity, timing, and popularity. Furthermore, the top three marketing strategies for BEMSs were found to be internet advertising strategies, discounts to consumers, and online sales. The analysis of the results has also offered valuable insights into the strengths and weaknesses of the studied BEMS provider, as well as the opportunities and threats present within the BEMS market.

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  • 9.
    Beheshtinia, Mohammad Ali
    et al.
    Industrial Engineering Department, Faculty of Engineering, Semnan University, Iran.
    Sedady, Fatima
    Industrial Engineering Department, Faculty of Engineering, Semnan University, Iran.
    Fathi, Masood
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment. Division of Industrial Engineering and Management, Department of Civil and Industrial Engineering, Uppsala University, Sweden.
    Ghobakhloo, Morteza
    Division of Industrial Engineering and Management, Department of Civil and Industrial Engineering, Uppsala University, Sweden ; School of Economics and Business, Kaunas University of Technology, Lithuania.
    Iranmanesh, Mohammad
    La Trobe Business School, La Trobe University, Melbourne, Victoria, Australia.
    A fuzzy three-dimensional house of quality to integrate and coordinate departments’ activities in organizations2023In: IEEE Access, E-ISSN 2169-3536Article in journal (Refereed)
    Abstract [en]

    This study aims to introduce a method to integrate and coordinate departments’ activities to enhance the service quality of organizations using Quality Function Deployment (QFD). To this purpose, the classical two-dimensional House Of Quality (HOQ) matrix is changed to a three-dimensional form (3D-HOQ). The 3D-HOQ is applied to the marketing and Human Resources (HR) departments of a bank to determine customers’ and employees’ demands, respectively. The 3D-HOQ is also employed to provide a unique list of technical requirements to satisfy the identified demands. Obtaining a unique list of technical requirements with the cooperation of both departments reduces the inconsistency between departments, saves cost and time by preventing reworks and parallel works, and increases the organization’s efficiency. Moreover, 3D-HOQ is combined with the SERVQUAL technique and fuzzy theory to determine the weight of obtained technical requirements. The study is conducted in four main steps, (1) identifying the customers’ and employees’ demands, (2) identifying the technical requirements for simultaneous satisfaction of both customers’ and employees’ demands, (3) determining the relationships between the technical requirements and the identified demands, and (4) prioritizing technical requirements. Applying the 3D-HOQ resulted in identifying 30 customers’ demands, 30 employees’ demands, and 50 technical requirements. The study results show that "using new banking technologies" has the highest weight among the customers’ demands, and "job security" has been found to have the highest weight among employees’ demands. Moreover, "Intra-organizational processes automation" has been identified as the technical requirement with the highest weight.

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  • 10.
    Chiet, Cheong Wen
    et al.
    Universiti Tunku Abdul Rahman, Malaysia.
    Ching, Ng Tan
    Universiti Tunku Abdul Rahman, Malaysia.
    Huat, Saw Lip
    Universiti Tunku Abdul Rahman, Malaysia.
    Fathi, Masood
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Tzuu, Tan Jaw
    Universiti Tunku Abdul Rahman, Malaysia.
    The Integration of Lean and Green Manufacturing for Malaysian Manufacturers: A Literature Review to Explore the Synergies between Lean and Green Model2019In: International Conference on Sustainable Energy and Green Technology 2018 / [ed] Chong Wen Tong, Wang Chin-Tsan, Bernard Saw Lip Huat, Institute of Physics Publishing (IOPP), 2019, Vol. 268, article id 012066Conference paper (Refereed)
    Abstract [en]

    In general, profitability and efficiency have been the main interest for organization. However, the increasing concerns for the environment from government, regulators, customers and other stakeholders has forced companies to seek for alternatives to achieve green objectives. The difficulties faced by organizations are lack of awareness and guideline in implementing green practices in their daily operation. Under constrained resources, employers are reluctant to spend money on something unclear. During the last decade, lean manufacturing seems to be visible trend in most of the manufacturing industries in Malaysia. As lean tends to emphasize on waste reduction, it provides similarity between lean and green. Therefore, it is a better atmosphere to deploy green practices and tools under existing lean manufacturing. The purpose of this paper is to present a review on the synergies between green and lean and identifying the determinants that affecting both lean and green manufacturing for Malaysian manufacturers. The determinant obtained are financial benefit, incentive, legislation, stakeholder, management commitment, technology, environmental awareness and brand image or competitiveness. Besides, the authors identified and suggested future research directions on developing an integrated lean-green model for daily operation. This study aims to assist researchers to identify the opportunities and challenges on lean-green model and this review is useful for manufacturers and government in developing manufacturing policies and guideline.

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  • 11.
    Fathi, Masood
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Fontes, Dalila Benedita Machado Martins
    University of Porto, Portugal / INESC TEC, Porto, Portugal.
    Urenda Moris, Matias
    Jönköping University, Jönköping, Sweden / Uppsala University, Sweden.
    Ghobakhloo, Morteza
    University of Hormozgan, Bandar Abbas, Iran.
    Assembly line balancing problem: a comparative evaluation of heuristics and a computational assessment of objectives2018In: Journal of Modelling in Management, ISSN 1746-5664, E-ISSN 1746-5672, Vol. 13, no 2, p. 455-474Article in journal (Refereed)
    Abstract [en]

    Purpose – The purpose of this study is to firstly investigate the efficiency of the most commonly used performance measures for minimizing the Number of Workstations (NWs) in approaches addressing Simple Assembly Line Balancing Problem (SALBP) for both straight and U-shaped line. Secondly, this study aims to provide a comparative evaluation of 20 constructive heuristics to find solutions to the SALBP-1.

    Design/methodology/approach – 200 problems are solved by 20 different constructive heuristics for both straight and U-shaped assembly line. Moreover, several comparisons have been made to evaluate the performance of constructive heuristics.

    Findings – Minimizing the Smoothness Index (SI) is not necessarily equivalent to minimizing the NWs, therefore, it should not be used as the fitness function in approaches addressing the SALBP-1. Line efficiency (LE) and the idle time (IT) are indeed reliable performance measures for minimizing the NWs. The most promising heuristics for straight and U-shaped line configurations for SALBP-1 are also ranked and introduced.

    Practical implications – Results are expected to help scholars and industrial practitioners to better design effective solution methods for having a most balance assembly line. This study will further help with choosing the most proper heuristic with regard to the problem specifications and line configuration.

    Originality/value – There is limited research assessing the efficiency of the common objectives for SALBP-1. This study is among the first to prove that minimizing the workload smoothness is not equivalent to minimizing the NWs in SALBP-1 studies. This work is also one of the first attempts for evaluating the constructive heuristics for both straight and U-shaped line configurations.

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  • 12.
    Fathi, Masood
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Ghobakhloo, Morteza
    Department of Industrial Engineering, Minab Higher Education Center, University of Hormozgan, Bandar Abbas, Iran / Modern Technology Development and Implementation Research Center, University of Hormozgan, Bandar Abbas, Iran.
    Syberfeldt, Anna
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    An Interpretive Structural Modeling of Teamwork Training in Higher Education2019In: Education Sciences, E-ISSN 2227-7102, Vol. 9, no 1, p. 1-20Article in journal (Refereed)
    Abstract [en]

    In the past decade, the importance of teamwork training in higher education and employers’ enthusiasm for recruiting team players have been widely discussed in the literature. Yet, the process through which effective teamwork training is developed in a higher education setting has not yet been properly discussed. The present study aims to map the precedence relationships among the key determinants of teamwork training effectiveness and explain the process through which an effective teamwork training program can be developed. The study first conducted an extensive review of the literature to highlight the key determinants of effective teamwork training. Next, the study benefitted from an interpretive structural modeling technique and captured the opinions of a group of teamwork training experts to further map the interrelationships among the potential determinants that were identified. By listing the key determinants of effective teamwork training, mapping their interrelationships, and identifying their driving and dependence power, the present study is expected to help practitioners and academicians through providing a detailed understanding of the process through which an effective teamwork training program can be developed in a higher education context.

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  • 13.
    Fathi, Masood
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Morteza, Ghobakhloo
    Department of Industrial Engineering, Minab Higher Education Center, University of Hormozgan, Bandar Abbas, Iran.
    Enabling Mass Customization and Manufacturing Sustainability in Industry 4.0 Context: A Novel Heuristic Algorithm for in-Plant Material Supply Optimization2020In: Sustainability, E-ISSN 2071-1050, Vol. 12, no 16, p. 1-15, article id 6669Article in journal (Refereed)
    Abstract [en]

    The fourth industrial revolution and the digital transformation of consumer markets require contemporary manufacturers to rethink and reshape their business models to deal with the ever-changing customer demands and market turbulence. Manufacturers nowadays are inclined toward product differentiation strategies and more customer-focused approaches to stay competitive in the Industry 4.0 environment, and mass customization and product diversification are among the most commonly implemented business models. Under such circumstances, an economical material supply to assembly lines has become a significant concern for manufacturers. Consequently, the present study deals with optimizing the material supply to mixed-model assembly lines that contribute to the overall production cost efficiency, mainly via the reduction of both the material transportation and material holding costs across production lines, while satisfying certain constraints. Given the complexity of the problem, a novel two-stage heuristic algorithm is developed in this study to enable a cost-efficient delivery. To assess the efficiency and effectiveness of the proposed heuristic algorithm, a set of test problems are solved and compared against the best solution found by a commercial solver. The results of the comparison reveal that the suggested heuristic provides reasonable solutions, thus offering immense opportunities for production cost efficiency and manufacturing sustainability under the mass customization philosophy.

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  • 14.
    Fathi, Masood
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Nourmohammadi, Amir
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Ghobakhloo, Morteza
    Department of Industrial Engineering, Minab Higher Education Center, University of Hormozgan, Bandar Abbas, Iran.
    Yousefi, Milad
    Department of Industrial Engineering and Transportation, Universidade Federal do Rio Grande do Sul—UFRGS, Porto Alegre, RS, Brazil.
    Production Sustainability via Supermarket Location Optimization in Assembly Lines2020In: Sustainability, E-ISSN 2071-1050, Vol. 12, no 11, p. 1-16, article id 4728Article in journal (Refereed)
    Abstract [en]

    Manufacturers worldwide are nowadays in pursuit of sustainability. In the Industry 4.0 era, it is a common practice to implement decentralized logistics areas, known as supermarkets, to achieve production sustainability via Just-in-Time material delivery at assembly lines. In this environment, manufacturers are commonly struggling with the Supermarket Location Problem (SLP), striving to efficiently decide on the number and location of supermarkets to minimize the logistics cost. To address this prevalent issue, this paper proposed a Simulated Annealing (SA) algorithm for minimizing the supermarket cost, via optimally locating supermarkets in assembly lines. The efficiency of the SA algorithm was tested by solving a set of test problems. In doing so, a holistic performance index, namely the total cost of supermarkets, was developed that included both shipment cost and the installation cost across the assembly line. The effect of workload balancing on the supermarket cost was also investigated in this study. For this purpose, the SLP was solved both before and after balancing the workload. The results of the comparison revealed that workload balancing could significantly reduce the total supermarket cost and contribute to the overall production and economic sustainability. It was also observed that the optimization of material shipment cost across the assembly line is the most influencing factor in reducing the total supermarket cost.

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  • 15.
    Fathi, Masood
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Nourmohammadi, Amir
    Department of Industrial & Systems Engineering, Tarbiat Modares University, Tehran, Iran.
    Ng, Amos H. C.
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Assembly Line Balancing Type-E with Technological Requirement: A Mathematical Model2018In: Advances in Manufacturing Technology XXXII: Proceedings of the 16th International Conference on Manufacturing Research, incorporating the 33rd National Conference on Manufacturing Research, September 11–13, 2018, University of Skövde, Sweden / [ed] Peter Thorvald, Keith Case, Amsterdam: IOS Press, 2018, Vol. 8, p. 183-188Conference paper (Refereed)
    Abstract [en]

    This study is motivated by a real-world assembly line in an automotive manufacturing company and it addresses the simple assembly line balancing problem type-E (SALBPE). The SALBPE aims to maximize the balance efficiency (BE) through determining the best combinations of cycle time and station number. To cope with the problem, a mixed integer nonlinear programming (MINLP) model is proposed. The MINLP model differs from the existing ALBPE models as it includes the technological requirements of assembly tasks and optimizes the variation of workload beside the BE. The validity of the proposed model is tested by solving the real-world case study and a set of benchmark problems.

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  • 16.
    Fathi, Masood
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Nourmohammadi, Amir
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Ng, Amos H. C.
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Syberfeldt, Anna
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    An optimization model for balancing assembly lines with stochastic task times and zoning constraints2019In: IEEE Access, E-ISSN 2169-3536, Vol. 7, p. 32537-32550, article id 8663269Article in journal (Refereed)
    Abstract [en]

    This study aims to bridge the gap between theory and practice by addressing a real-world assembly line balancing problem (ALBP) where task times are stochastic and there are zoning constraints in addition to the commonly known ALBP constraints. A mixed integer programming (MIP) model is proposed for each of the straight and U-shaped assembly line configurations. The primary objective in both cases is to minimize the number of stations; minimizing the maximum of stations’ mean time and the stations’ time variance are considered secondary objectives. Four different scenarios are discussed for each model, with differences in the objective function. The models are validated by solving a real case taken from an automobile manufacturing company and some standard test problems available in the literature. The results indicate that both models are able to provide optimum solutions for problems of different sizes. The technique for order preference by similarity to ideal solution (TOPSIS) is used to create reliable comparisons of the different scenarios and valid analysis of the results. Finally, some insights regarding the selection of straight and U-shaped layouts are provided.

  • 17.
    Fathi, Masood
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Nourmohammadi, Amir
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Ng, Amos H. C.
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Syberfeldt, Anna
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Eskandari, Hamidreza
    Faculty of Management and Economics, Tarbiat Modares University, Tehran, Iran.
    An improved genetic algorithm with variable neighborhood search to solve the assembly line balancing problem2020In: Engineering computations, ISSN 0264-4401, E-ISSN 1758-7077, Vol. 37, no 2, p. 501-521Article in journal (Refereed)
    Abstract [en]
    • Purpose – This study aims to propose an efficient optimization algorithm to solve the assembly line balancing problem (ALBP). The ALBP arises in high-volume, lean production systems when decision makers aim to design an efficient assembly line while satisfying a set of constraints.
    • Design/methodology/approach – An improved genetic algorithm (IGA) is proposed in this study to deal with ALBP in order to optimize the number of stations and the workload smoothness.
    • Findings – To evaluate the performance of the IGA, it is used to solve a set of well-known benchmark problems and a real-life problem faced by an automobile manufacturer. The solutions obtained are compared against two existing algorithms in the literature and the basic genetic algorithm. The comparisons show the high efficiency and effectiveness of the IGA in dealing with ALBPs.
    • Originality/value – The proposed IGA benefits from a novel generation transfer mechanism that improves the diversification capability of the algorithm by allowing population transfer between different generations. In addition, an effective variable neighborhood search is employed in the IGA to enhance its local search capability.
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  • 18.
    Fathi, Masood
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Syberfeldt, Anna
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Ghobakhloo, Morteza
    University of Hormozgan, Bandar Abbas, Iran.
    Eskandari, Hamidreza
    Tarbiat Modares University, Tehran, Iran.
    An optimization model for material supply scheduling at mixed-model assembly lines2018In: Procedia CIRP, ISSN 2212-8271, E-ISSN 2212-8271, Vol. 72, p. 6p. 1258-1263Article in journal (Refereed)
    Abstract [en]

    This study is motivated by a real case study and addresses the material supply problem at assembly lines. The aim of the study is to optimally schedule the delivery of raw material at assembly lines while using the minimum number of vehicles. To cope with the problem an original mixed integer linear programming model has been proposed based on the assumptions and constraints observed in the case study. The validity of the model has been examined by solving several real cases and analysing different scenarios. The results of the study show the efficiency and effectiveness of the model.

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  • 19.
    Ghobakhloo, Morteza
    et al.
    Department of Industrial Engineering, Minab Higher Educational Center, University of Hormozgan, Bandar Abbas, Iran.
    Azar, Adel
    Department of Management and Economics, Tarbiat Modares University, Tehran, Iran.
    Fathi, Masood
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Lean-green manufacturing: the enabling role of information technology resource2018In: Kybernetes, ISSN 0368-492X, E-ISSN 1758-7883, Vol. 47, no 9, p. 1752-1777Article in journal (Refereed)
    Abstract [en]

    Purpose – The purpose of this paper is to contribute to the existing knowledge about the relationships between information technology (IT), lean manufacturing (LM), organizational environmental issues and business performance.

    Design/methodology/approach – A questionnaire-based survey was conducted to collect data from 122 elite manufacturers, and the hypothesized relationships were tested using partial least squares structural equation modeling. Findings – IT competence in LM acts as a lower-order organizational capability, and its business value should be recognized through the intermediate roles of LM effectiveness and environmental management capability. Findings recommend that the net benefits of LM are mainly materialized through waste and pollution reduction and simplified implementation of proactive environmental practices.

    Research limitations/implications – Among other limitations, relying on a rather small sample size and cross-sectional data of this research, and lack of generalizability of findings, tends to have certain limitations. An interesting direction for future research would be to extend this research by assessing interaction of other types of IT resources with LM and organizational environmental issues.

    Practical implications – Both LM and proactive environmental management are information-intensive. Investment in both technological and human aspects of IT resource aimed at increasing the effectiveness of LM activities and proactive environmental practices is imperative for contemporary manufacturers.

    Originality/value – This study introduces the IT capability of IT competence in LM and two organizational capabilities of LM effectiveness and environmental management capability. By doing so, the study highlights the significant role of organizational environmental issues in devising firms’ IT and advanced manufacturing technology investment strategies in LM context.

  • 20.
    Ghobakhloo, Morteza
    et al.
    Department of Industrial Engineering, University of Hormozgan, Bandar Abbas, Iran / Department of Mechanical and Manufacturing Engineering, University Putra Malaysia, Serdang, Malaysia.
    Fathi, Masood
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Corporate survival in Industry 4.0 era: the enabling role of lean-digitized manufacturing2019In: Journal of Manufacturing Technology Management, ISSN 1741-038X, E-ISSN 1758-7786, Vol. 31, no 1, p. 1-30Article in journal (Refereed)
    Abstract [en]

    purpose– The study demonstrates how small manufacturing firms can leverage their Information Technology (IT) resources to develop the lean-digitized manufacturing system that offers sustained competitiveness in the Industry 4.0 era.

    Design/methodology/approach – The study performs an in-depth 5-years case study of a manufacturing firm, and reports its journey from failure in the implementation of enterprise resource planning to its success in integrating IT-based technology trends of Industry 4.0 with the firm’s core capabilities and competencies while pursuing manufacturing digitization.

    Findings – Industry 4.0 transition requires the organizational integration of many IT-based modern technologies and the digitization of entire value chains. However, Industry 4.0 transition for smaller manufacturers can begin with digitization of certain areas of operations in support of organizational core strategies. Development of leandigitized manufacturing system is a viable business strategy for corporate survivability in the Industry 4.0 setting.

    Research limitations/implications – Although the implementation of lean-digitized manufacturing system is costly and challenging, this manufacturing strategy offers superior corporate competitiveness in the long run. Since this finding is rather limited to the present case study, assessing the business value of lean-digitized manufacturing system in a larger-scale research context would be an interesting avenue for future research.

    Practical implications – Industry 4.0 transition for typical manufacturers should commensurate with their organizational, operational, and technical particularities. Digitization of certain operations and processes, when aligned with the firm’s core strategies, capabilities, and procedures, can offer superior competitiveness even in Industry 4.0 era, meaning that the strategic plan for successful Industry 4.0 transition is idiosyncratic to each particular manufacturer.

    Social implications – Manufacturing digitization can have deep social implications as it alters inter and intra organizational relationships, causes unemployment among low-skilled workforce, and raises data security and privacy concerns. Manufacturers should take responsibility for their digitization process and steer it in a direction that simultaneously safeguards economic, social, and environmental sustainability.

    Originality/value – The strategic roadmap devised and employed by the case company for managing its digitization process can better reveal what manufacturing digitization, mandated by Industry 4.0, might require of typical manufacturers, and further enable them to better facilitate their digital transformation process.

  • 21.
    Ghobakhloo, Morteza
    et al.
    School of Economics and Business, Kaunas University of Technology, Lithuania.
    Fathi, Masood
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment. Division of Industrial Engineering and Management, Uppsala University, Sweden.
    Industry 4.0 and opportunities for energy sustainability2021In: Journal of Cleaner Production, ISSN 0959-6526, E-ISSN 1879-1786, Vol. 295, article id 126427Article in journal (Refereed)
    Abstract [en]

    Understanding the interactions of Industry 4.0 and sustainability is a cutting-edge research topic. The present study aims to contribute to this research topic by explaining how Industry 4.0 may contribute to energy sustainability. The present study performs a content-centric qualitative review of the extant digitalization literature to identify the primary energy sustainability functions of Industry 4.0. The interpretive structural modeling technique is further used for mapping the interrelationships among various energy sustainability functions identified. The interpretive model developed, and the Matrice d'Impacts Croisés Multiplication Appliquée àun Classement analysis offered exciting insights into the Industry 4.0-energy sustainability interactions. Findings show that Industry 4.0 promotes energy sustainability via a very complex mechanism that involves ten interrelated functions. Contrary to the general opinion, production efficiency offered by the digitalization of the manufacturing industry is not the immediate and most essential energy efficiency outcome of the digital industrial transformation. Industry 4.0 primarily contributes to energy sustainability by enabling the energy industry to reshape its operating landscape and enjoy more advanced, intelligent, and complicated energy production and distribution equipment. The digitalization of the energy demand sector, digitalization of the manufacturing industry, and the introduction of smarter and more sustainable products are among the main opportunities of Industry 4.0 for energy sustainability. Overall, the study and the ISM model of energy sustainability developed explains how Industry 4.0 contributes to energy sustainability via different functions and how each function is placed within the structural model based on its driving and dependence powers.

  • 22.
    Ghobakhloo, Morteza
    et al.
    Department of Industrial Engineering, Minab Higher Education Center, University of Hormozgan, Bandar Abbas, Iran / Modern Technology Development and Implementation Research Center, University of Hormozgan, Bandar Abbas, Iran.
    Fathi, Masood
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Modeling the Success of Application-Based Mobile Banking2019In: Economies, ISSN 2227-7099, Vol. 7, no 4, p. 1-21, article id 114Article in journal (Refereed)
    Abstract [en]

    The present study addresses the issue of mobile banking customer retention by developing and empirically testing a theoretical model that describes the way mobile banking success is achieved. The data collection process was conducted via a web-based questionnaire survey through which 402 usable responses from users of application-based mobile banking services were collected. The data collected were further analyzed via covariance-based structural equation modeling. Results indicate that application-based mobile banking success can be defined in terms of the favorable attitude toward and repeated use of mobile banking applications. Experienced advantage, user satisfaction, and post-use trust toward mobile banking applications are among the critical enablers of application-based mobile banking success. The findings of this research can enable academicians and practitioners, banks, and financial institutions, in particular, to devise the mechanism through which the success of application-based mobile banking services can be facilitated.

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  • 23.
    Ghobakhloo, Morteza
    et al.
    Department of Industrial Engineering, Minab Higher Educational Center, University of Hormozgan, Bandar Abbas, Iran.
    Fathi, Masood
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Fontes, Dalila Benedita Machado Martins
    Faculty of Economics, Universidade do Porto, Porto, Portugal.
    Ching, Ng Tan
    Department of Mechanical and Material Engineering, Universiti Tunku Abdul Rahman - Kuala Lumpur Campus, Kuala Lumpur, Malaysia.
    Modeling lean manufacturing success2018In: Journal of Modelling in Management, ISSN 1746-5664, E-ISSN 1746-5672, Vol. 13, no 4, p. 908-931Article in journal (Refereed)
    Abstract [en]

    Purpose – The purpose of this study is to contribute to the existing knowledge about the process ofachieving Lean Manufacturing (LM) success.

    Design/methodology/approach – This study uses interpretive structural modeling and captures theopinions of a group of LM experts from a world-class Japanese automobile manufacturer, to map theinterrelationships among potential determinants of LM success. This study further uses the data from asurvey of 122 leading automobile part manufacturers by performing structural equation modeling toempirically test the research model proposed.

    Findings – Management support and commitment, financial resources availability, information technologycompetence for LM, human resources management, production process simplicity, supportive culture andsupply chain-wide integration are the key determinants that directly or indirectly determine the level ofachievement of LMsuccess.

    Research limitations/implications – The determinants of LM success as experienced by Asianautomobile manufacturers might be different from determinants of LM success as experienced byWestern automobile manufacturers. An interesting direction for future research would be to capturethe experts’ inputs from Western automobile manufacturers to complement the findings of thisstudy.

    Practical implications – The practical contribution of this study lays in the development of linkagesamong various LM success determinants. Utility of the proposed interpretive structural modeling andstructural equation modeling methodologies imposing order, direction and significance of therelationships among elements of LM success assumes considerable value to the decision-makers and LMpractitioners.

    Originality/value – Building on opinions of a group of LM experts and a case study of leading auto partmanufacturers, the present study strives to model the success of LM, a topic that has received little attentionto date.

  • 24.
    Ghobakhloo, Morteza
    et al.
    School of Economics and Business, Kaunas University of Technology, Lithuania.
    Fathi, Masood
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment. Division of Industrial Engineering and Management, Uppsala University, Sweden.
    Iranmanesh, Mohammad
    School of Business and Law, Edith Cowan University, Joondalup, WA, Australia.
    Maroufkhani, Parisa
    IntelliLab.org, Business School, Sherbrooke (Quebec), Canada.
    Morales, Manuel E.
    School of Economics and Business, Kaunas University of Technology, Lithuania.
    Industry 4.0 ten years on: A bibliometric and systematic review of concepts, sustainability value drivers, and success determinants2021In: Journal of Cleaner Production, ISSN 0959-6526, E-ISSN 1879-1786, Vol. 302, article id 127052Article, review/survey (Refereed)
    Abstract [en]

    The fourth industrial revolution, known as Industry 4.0, and the underlying digital transformation, is a cutting-edge research topic across various disciplines. Industry 4.0 literature is growing exponentially, overexpanding the current understanding of the digital industrial revolution through thousands of academic publications. This unprecedented growth calls for a systematic review of the concept, scope, definition, and functionality of Industry 4.0. Such systematic review should address the existing ambiguities and deliver a clear, comprehensive, and up-to-date overview of this phenomenon, including the possible implications for sustainability. Consistently, the present study carried out a systematic literature review of related articles, published online within the Industry 4.0 discipline until November 2020. The systematic literature review identified 745 eligible articles and applied extensive qualitative and quantitative data analysis methodically. The study provides a descriptive assessment of eligible articles’ properties and offers a unified conceptualization of Industry 4.0 and the underlying building blocks. The study explains how the implications of Industry 4.0 for value creation expand beyond the manufacturing industry. The study further describes the sustainability value drivers of the fourth industrial revolution and identifies the conditions on which digital industrial transformation success lays. Overall, findings reveal that Industry 4.0 transformation could address pressing issues of sustainable development goals, particularly concerning the manufacturing-economic development. The study also draws on the findings and offers important theoretical and practical implications, highlights the existing gaps within the literature, and discusses the possible future research directions.

  • 25.
    Ghobakhloo, Morteza
    et al.
    School of Economics and Business, Kaunas University of Technology, Lithuania.
    Fathi, Masood
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment. Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Civil and Industrial Engineering, Industrial Engineering and Management, Sweden.
    Maroufkhani, Parisa
    Zhejiang University, China.
    Industry 4.0 and SME Development: The Case of a Middle Eastern Country2022In: Industry 4.0 in SMEs Across the Globe: Drivers, Barriers, and Opportunities / [ed] Julian M. Müller; Nikolai Kazantsev, Boca Raton: CRC Press, 2022, 1, p. 177-190Chapter in book (Refereed)
    Abstract [en]

    Globalization, market turbulence, and global crisis such as the COVID-19 pandemic push the manufacturing industry to rush towards automation, data-centricity, and greater interconnectivity under the ongoing digital industrial transformation known as Industry 4.0. Smaller manufactures worldwide strive to keep up with the digitalization race and secure sustainable competitiveness. Fierce competition and market turbulence force Middle Eastern manufacturers to make the most of the digitalization race. The present study reports on the Industry 4.0 digital transformation and development of small and medium-sized manufacturing enterprises in Iran, one of the most economically influential countries within the Middle East. Smaller manufacturers in Iran consider Industry 4.0 to improve productivity, operate in the data-driven economy, and increase business resilience. Although the implementation rate of generic digital technologies has been somewhat promising among Iranian manufacturers, the present report identifies significant barriers slowing the implementation rate of more advanced Industry 4.0 technologies such as predictive analytics and blockchain technology. Overall, Industry 4.0 transformation has provided Iranian manufacturing enterprises with meaningful opportunities and benefits. Nonetheless, smaller manufacturers cannot generally develop an all-inclusive strategic plan for navigating digitalization efforts. This issue, along with many other barriers such as resource scarcity, digitalization immaturity, and cybersecurity risks, has slowed down the digital transformation of the Iranian manufacturing industry.

  • 26.
    Khamnei, Hossein Jabbari
    et al.
    Department of Statistics, Faculty of Mathematics-Statistics and Computer Science, University of Tabriz, Iran.
    Meidute-Kavaliauskiene, Ieva
    Faculty of Business Management, Vilnius Gediminas Technical University, Vilnius, Lithuania.
    Fathi, Masood
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment. Division of Industrial Engineering and Management, Department of Civil and Industrial Engineering, Uppsala University, Sweden.
    Valackienė, Asta
    Institute of Business and Economics, Faculty of Public Governance and Business, Mykolas Romeris University, Vilnius, Lithuania.
    Ghorbani, Shahryar
    Production Management Department, University of Sakarya, Turkey.
    Parameter Estimation of the Exponentiated Pareto Distribution Using Ranked Set Sampling and Simple Random Sampling2022In: Axioms, E-ISSN 2075-1680, Vol. 11, no 6, p. 1-9, article id 293Article in journal (Refereed)
    Abstract [en]

    In this paper, we have considered that ranked set sampling is able to estimate the parameters of exponentiated Pareto distribution. The method with which the maximum likelihood estimators for the parameters of exponentiated Pareto distribution is studied is numerical since there is no presence or possibility of a closed-form at the hands of estimators or any other intellectual. The numerical approach is a well-suited one for this study as there has been struggles in achieving it with any other technique. In order to compare the different sampling methods, simulation studies are performed as the main technique. As for the illustrative purposes, analysis of a simulated dataset is desired for the objective of the presentation. The conclusion that we can reach based on these is that the estimators based on the ranked set sample have far better efficiency than the simple random sample at the same sample size.

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  • 27.
    Khamnei, Hossein Jabbari
    et al.
    Department of Statistics, Faculty of Mathematics ; Statistics and computer Science, University of Tabriz, Iran.
    Nikannia, Sajad
    Department of Economic, Faculty of Economic and Management, University of Tabriz, Iran.
    Fathi, Masood
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment. Division of Industrial Engineering and Management, Department of Civil and Industrial Engineering, Uppsala University, Sweden.
    Ghorbani, Shahryar
    Production Management Department, University of Sakarya, Turkey.
    Modeling income distribution: An econophysics approach2023In: Mathematical Biosciences and Engineering, ISSN 1547-1063, E-ISSN 1551-0018, Vol. 20, no 7, p. 13171-13181Article in journal (Refereed)
    Abstract [en]

    This study aims to develop appropriate models for income distribution in Iran using the econophysics approach for the 2006–2018 period. For this purpose, the three improved distributions of the Pareto, Lognormal, and Gibbs-Boltzmann distributions are analyzed with the data extracted from the target household income expansion plan of the statistical centers in Iran. The research results indicate that the income distribution in Iran does not follow the Pareto and Lognormal distributions in most of the study years but follows the generalized Gibbs-Boltzmann distribution function in all study years. According to the results, the generalized Gibbs-Boltzmann distribution also properly fits the actual data distribution and could clearly explain the income distribution in Iran. The generalized Gibbs-Boltzmann distribution also fits the actual income data better than both Pareto and Lognormal distributions

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  • 28.
    Khanfar, Ahmad A. A.
    et al.
    School of Business and Law, Edith Cowan University, Joondalup, Australia.
    Iranmanesh, Mohammad
    School of Business and Law, Edith Cowan University, Joondalup, Australia.
    Ghobakhloo, Morteza
    School of Economics and Business, Kaunas University of Technology, Lithuania ; Graduate School of Business, Universiti Sains Malaysia, Penang, Malaysia.
    Senali, Madugoda Gunaratnege
    School of Arts and Humanities, Edith Cowan University, Joondalup, Australia.
    Fathi, Masood
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment. Division of Industrial Engineering and Management, Uppsala University, Sweden.
    Applications of Blockchain Technology in Sustainable Manufacturing and Supply Chain Management: A Systematic Review2021In: Sustainability, E-ISSN 2071-1050, Vol. 13, no 14, p. 1-20, article id 7870Article, review/survey (Refereed)
    Abstract [en]

    Developing sustainable products and processes is essential for the survival of manufacturers in the current competitive market and the industry 4.0 era. The activities of manufacturers andtheir supply chain partners should be aligned with sustainable development goals. Manufacturershave faced many barriers and challenges in implementing sustainable practices along the entiresupply chain due to globalisation, outsourcing, and offshoring. Blockchain technology has thepotential to address the challenges of sustainability. This study aims to explain the applications ofblockchain technology to sustainable manufacturing. We conducted a systematic literature reviewand explained the potential contributions of blockchain technology to the economic, environmental,and social performances of manufacturers and their supply chains. The findings of the study extendour understanding of the blockchain applications in sustainable manufacturing and sustainablesupply chains. Furthermore, the study explains how blockchain can influence the sustainable performance of manufacturers by creating transparency, traceability, real-time information sharing, andsecurity of the data capabilities.

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  • 29.
    Khodabandelou, Rouhollah
    et al.
    Department of Instructional and Learning Technologies, College of Education, Sultan Qaboos University, Muscat, Oman.
    Fathi, Masood
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment. Division of Industrial Engineering and Management, Uppsala University, Sweden.
    Amerian, Mohammad
    Allameh Tabataba'i University, Tehran, Islamic Republic of Iran.
    Fakhraie, Mohammad Reza
    National Iranian Oil Company, Tehran, Islamic Republic of Iran.
    A comprehensive analysis of the 21st century's research trends in English Mobile Learning: a bibliographic review of the literature2022In: The international journal of information and learning technology, ISSN 2056-4880, E-ISSN 2056-4899, Vol. 39, no 1, p. 29-49Article, review/survey (Refereed)
    Abstract [en]

    Purpose This study examines the importance of English Mobile Learning research as a foundation for lifelong and sustainable education from different points of view, including those of technology innovation experts, psychologists and educators. It aims to explore the current status and relevant research trends through the application of bibliometric mapping and bibliometric analysis.

    Design/methodology/approach For this study, all Web of Science records (in total 5,343) from 2000 to 2020 in the field of English Mobile Learning were analyzed using the VOSviewer and CiteSpace software tools. The WoS built-in functions, including “Refine” and “Analyze,” were employed to perform the bibliometric analysis. The study further analyzed a sample of the five most-cited articles to identify the previous studies with the highest quality or impact.

    Findings The results showed that research in English Mobile Learning is growing quickly and steadily with a noticeable emphasis on various device-based technologies and applications. The study also discusses the key implications for research institutions, education policymakers and academicians, and identifies the most prominent avenues for future research on English Mobile Learning. Moreover, the results shared in this review highlight the most important and emerging areas of research in the field.

    Originality/value This article is the most recent bibliographic review of literature that particularly addresses the English Mobile Learning research during the past two decades.

  • 30.
    Mahmoodi, Ehsan
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Fathi, Masood
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment. Division of Industrial Engineering and Management, Department of Civil and Industrial Engineering, Uppsala University, Sweden.
    Ghobakhloo, Morteza
    Division of Industrial Engineering and Management, Department of Civil and Industrial Engineering, Uppsala University, Sweden ; School of Economics and Business, Kaunas University of Technology, Lithuania.
    The impact of Industry 4.0 on bottleneck analysis in production and manufacturing: Current trends and future perspectives2022In: Computers & industrial engineering, ISSN 0360-8352, E-ISSN 1879-0550, Vol. 174, article id 108801Article, review/survey (Refereed)
    Abstract [en]

    Bottleneck analysis, known as one of the essential lean manufacturing concepts, has been extensively researched in the literature. Recently, there has been a move towards using new Industry 4.0-based concepts and technologies in the development of bottleneck analysis. However, the interrelations between bottleneck analysis and Industry 4.0 have not been studied thoroughly. The present study addresses this gap and performs a systematic literature review on articles available in major scientific databases (i.e., Web of Science and Scopus) to investigate the impact of Industry 4.0 on the advancement of bottleneck analysis in production and manufacturing. Bibliometric analysis and content review were performed to extract the quantitative and qualitative data. Results revealed that only five out of 15 design principles and five out of eleven technologies of Industry 4.0 were addressed previously in developing bottleneck analysis methods. In addition to highlighting the existing gaps in the literature and proposing topics for future research, several potential development streams are proposed by studying the design principles and technologies of Industry 4.0, which have not been considered in bottleneck analysis before.

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  • 31.
    Mahmoodi, Ehsan
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Fathi, Masood
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment. Division of Industrial Engineering and Management, Uppsala University, Sweden.
    Tavana, Madjid
    Business Systems and Analytics Department, Distinguished Chair of Business Analytics, La Salle University, Philadelphia, USA ; Business Information Systems Department, Faculty of Business Administration and Economics, University of Paderborn, Germany.
    Ghobakhloo, Morteza
    Division of Industrial Engineering and Management, Uppsala University, Sweden.
    Ng, Amos H. C.
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment. Division of Industrial Engineering and Management, Uppsala University, Sweden.
    Data-driven simulation-based decision support system for resource allocation in industry 4.0 and smart manufacturing2024In: Journal of manufacturing systems, ISSN 0278-6125, E-ISSN 1878-6642, Vol. 72, p. 287-307Article in journal (Refereed)
    Abstract [en]

    Data-driven simulation (DDS) is fundamental to analytical and decision-support technologies in Industry 4.0 and smart manufacturing. This study investigates the potential of DDS for resource allocation (RA) in high-mix, low-volume smart manufacturing systems with mixed automation levels. A DDS-based decision support system (DDS-DSS) is developed by incorporating two RA strategies: simulation-based bottleneck analysis (SB-BA) and simulation-based multi-objective optimization (SB-MOO). To enhance the performance of SB-MOO, a unique meta-learning mechanism featuring memory, dynamic orthogonal array, and learning rate is integrated into the NSGA-II, resulting in a modified version of the NSGA-II with meta-learning (i.e., NSGA-II-ML). The proposed DSS also benefits from a post-optimality analysis that leverages a clustering algorithm to derive actionable insights. A real-life marine engine manufacturing application study is presented to demonstrate the applicability and exhibit efficacy of the proposed DSS and NSGA-II-ML. To this aim, NSGA-II-ML was tested against the original NSGA-II and differential evolution (DE) algorithm across a set of test problems. The results revealed that NSGA-II-ML surpassed the other two in terms of the number of non-dominated solutions and hypervolume, particularly in medium and large-sized problems. Furthermore, NSGA-II-ML achieved a 24% improvement in the best throughput found in the real case problem, outperforming SB-BA, NSGA-II, and DE. The post-optimality analysis led to the extraction of valuable knowledge about the key, influencing decision variables on the throughput.

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  • 32.
    Masoomi, Behzad
    et al.
    Department of Industrial Management, Islamic Azad University, Firoozkooh Branch, Tehran, Iran.
    Ghasemian Sahebi, Iman
    Department of Industrial Management, Faculty of Management, University of Tehran, Iran.
    Fathi, Masood
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment. Division of Industrial Engineering and Management, Department of Civil and Industrial Engineering, Uppsala University, Sweden.
    Yıldırım, Figen
    International Trade Department, Istanbul Commerce University, Turkey.
    Ghorbani, Shahryar
    Production Management Department, University of Sakarya, Turkey.
    Strategic supplier selection for renewable energy supply chain under green capabilities (fuzzy BWM-WASPAS-COPRAS approach)2022In: Energy Strategy Reviews, ISSN 2211-467X, E-ISSN 2211-4688, Vol. 40, article id 100815Article in journal (Refereed)
    Abstract [en]

    The supplier selection problem (SSP) is a significant issue in renewable supply chain management (RSCM). Selecting a strategic green supplier can not only discover the sustainable development of supply chains but also optimize the consumption rate of resources and decrease the negative environmental effects, which adopts to the green development context. As a multiple criteria group decision-making (MCGDM) problem, choosing a strategic green supplier is important to renewable supply chains. However, how to choose a strategic green supplier for supply chains is a great effort. Hence, In the present work, evaluating a set of strategic suppliers is primarily based on green capabilities by using an integrated fuzzy Best Worst Method (FBWM) with the other two techniques, namely COPRAS (Complex Proportional Assessment of Alternatives) and WASPAS (Weighted Aggregated Sum-Product Assessment). Initially, nine strategic supplier selection criteria have been identified through literature review and a real-world case study of Iran's renewable energy supply chain is deliberated to exhibit the proposed framework's applicability. The applied methodology and its analysis will provide insight to decision-makers of strategic supplier selection. It may aid decision-makers and the procurement department in differentiating the significant strategic green supplier selection criteria and assess the strategic green supplier in the local and global market supply chain. Finally, the strengths and limitation of the framework are discussed by using comparative analysis with other methods.

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  • 33.
    Ng, Tan Ching
    et al.
    Department of Mechanical and Material Engineering, Universiti Tunku Abdul Rahman, Kajang, Malaysia.
    Lau, Sie Yee
    Department of Mechanical and Material Engineering, Universiti Tunku Abdul Rahman, Kajang, Malaysia ; Mechanical Engineering Programme, University of Technology Sarawak, Sibu, Malaysia.
    Ghobakhloo, Morteza
    School of Economics and Business, Kaunas University of Technology, Lithuania ; Graduate School of Business, Universiti Sains Malaysia, Gelugor, Malaysia.
    Fathi, Masood
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment. Division of Industrial Engineering and Management, Uppsala University, Sweden.
    Liang, Meng Suan
    Department of Mechanical and Material Engineering, Universiti Tunku Abdul Rahman, Kajang, Malaysia.
    The Application of Industry 4.0 Technological Constituents forSustainable Manufacturing: A Content-Centric Review2022In: Sustainability, E-ISSN 2071-1050, Vol. 14, no 7, p. 1-21, article id 4327Article, review/survey (Refereed)
    Abstract [en]

    Industry 4.0 has been associated with the rise of disruptive intelligence and informationtechnologies. These cutting-edge technologies have the potential to increase productivity whilesimultaneously having a significant impact on social and environmental sustainability. As a result,manufacturers must evaluate the role of these innovative technologies in sustainable development,as these technologies have the potential to address prevalent sustainability issues. A content-centricstudy of the implementation of these Industry 4.0 cutting-edge technologies in sustainable manufacturing is currently absent. A systematic literature study was conducted to explain the potentialcontribution of these novel technologies to the economic, social, and environmental dimensions ofmanufacturing industries. This study describes how these cutting-edge technologies are used insustainable manufacturing. The findings of this study are particularly beneficial to practitioners whoseek to apply one or more digital technologies to sustainable development.

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  • 34.
    Nourmohammadi, Amir
    et al.
    Faculty of Industrial & Systems Engineering, Tarbiat Modares University, Tehran, Iran.
    Eskandari, Hamidreza
    Iran Management & Technology Development Center, Tarbiat Modares University, Tehran, Iran.
    Fathi, Masood
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Design of stochastic assembly lines considering line balancing and part feeding with supermarkets2019In: Engineering optimization (Print), ISSN 0305-215X, E-ISSN 1029-0273, Vol. 51, no 1, p. 63-83Article in journal (Refereed)
    Abstract [en]

    This article aims to address the assembly line balancing problem (ALBP) and supermarket location problem (SLP) as two long-term interrelated decision problems considering the stochastic nature of the task times and demands. These problems arise in real-world assembly lines during the strategic decision-making phase of configuring new assembly lines from both line balancing and part-feeding (PF) aspects. A hierarchical mathematical programming model is developed, in which the first level resolves the stochastic ALBP by minimizing the workstation numbers and the second level deals with the stochastic SLP while optimizing the PF shipment, inventory and installation costs. The results of case data from an automotive parts manufacturer and a set of standard test problems verified that the proposed model can optimize the configuration of assembly lines considering both ALBP and SLP performance measures. This study also validates the effect of the stochastic ALBP on the resulting SLP solutions.

  • 35.
    Nourmohammadi, Amir
    et al.
    Tarbiat Modares University, Tehran, Iran.
    Eskandari, Hamidreza
    Tarbiat Modares University, Tehran, Iran.
    Fathi, Masood
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Aghdasi, Mohammad
    Tarbiat Modares University, Tehran, Iran.
    A mathematical model for supermarket location problem with stochastic station demands2018In: Procedia CIRP, ISSN 2212-8271, E-ISSN 2212-8271, Vol. 72, p. 6p. 444-449Article in journal (Refereed)
    Abstract [en]

    This paper aims to investigate the effect of station demands variations on supermarket location problem (SLP). This problem arises in the real-world assembly line part feeding (PF) context where supermarkets are used as the intermediate storage areas for stations. To this purpose a stochastic SLP model is developed to optimize the total cost of PF in terms of shipment, inventory and installation costs. The computational results over a real case as well as different test instances verify that the station demands variation has an effect on the SLP solutions.

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  • 36.
    Nourmohammadi, Amir
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. Faculty of Industrial & Systems Engineering, Tarbiat Modares University, Tehran, Iran.
    Eskandari, Hamidreza
    Faculty of Management and Economics, Tarbiat Modares University, Tehran, Iran / School of Management, Swansea University, UK.
    Fathi, Masood
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Ng, Amos H. C.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Integrated locating in-house logistics areas and transport vehicles selection problem in assembly lines2021In: International Journal of Production Research, ISSN 0020-7543, E-ISSN 1366-588X, Vol. 59, no 2, p. 598-616Article in journal (Refereed)
    Abstract [en]

    Decentralised in-house logistics areas, known as supermarkets, are widely used in the manufacturing industry for parts feeding to assembly lines. In contrary to the literature and inspired by observation in a real case, this study relaxes the assumption of using identical transport vehicles when deciding on the supermarkets’ location by considering the availability of different vehicles. In this regard, this study deals with the integrated supermarket location and transport vehicles selection problems (SLTVSP). A mixed-integer programming (MIP) model of the problem is developed. Due to the complexity of the problem, a hybrid genetic algorithm (GA) with variable neighborhood search (GA-VNS) is also proposed to address large-sized problems. The performance of GA-VNS is compared against the MIP, the basic GA, and simulated annealing (SA) algorithm. The computational results from the real case and a set of generated test problems show that GA-VNS provides a very good approximation of the MIP solutions at a much shorter computational time while outperforming the other compared algorithms. The analysis of the results reveals that it is beneficial to apply different transport vehicles rather than identical vehicles for SLTVSP.

  • 37.
    Nourmohammadi, Amir
    et al.
    Tarbiat Modares University, Tehran, Iran.
    Eskandari, Hamidreza
    Tarbiat Modares University, Tehran, Iran.
    Fathi, Masood
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Ranjbar Bourani, Mehdi
    University of Science & Technology of Mazandaran, Behshahr, Iran.
    An integrated model for cost-oriented assembly line balancing and parts feeding with supermarkets2018In: Procedia CIRP, ISSN 2212-8271, E-ISSN 2212-8271, Vol. 72, p. 5p. 381-385Article in journal (Refereed)
    Abstract [en]

    This paper aims to deal with assembly line design from both line balancing and parts feeding (PF) aspects as two-interrelated decision problems while supermarkets are used. These problems arise in the real-world assembly lines (ALs) where decision makers are planning to simultaneously determine the optimal number of stations and the optimal number of supermarkets so that the total installation costs of ALs including line balancing and PF costs are minimized. To this purpose an integrated mathematical model is proposed and its performance is tested through solving a number of benchmark problems and a real case taken from industry.

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  • 38.
    Nourmohammadi, Amir
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Fathi, Masood
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment. Division of Industrial Engineering and Management, Uppsala University, Sweden.
    Ng, Amos H. C.
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment. Division of Industrial Engineering and Management, Uppsala University, Sweden.
    Balancing and scheduling assembly lines with human-robot collaboration tasks2022In: Computers & Operations Research, ISSN 0305-0548, E-ISSN 1873-765X, Vol. 140, p. 1-18, article id 105674Article in journal (Refereed)
    Abstract [en]

    In light of the Industry 5.0 trend towards human-centric and resilient industries, human-robot collaboration (HRC) assembly lines can be used to enhance productivity and workers’ well-being, provided that the optimal allocation of tasks and available resources can be determined. This study investigates the assembly line balancing problem (ALBP), considering HRC. This problem, abbreviated ALBP-HRC, arises in advanced manufacturing systems, where humans and collaborative robots share the same workplace and can simultaneously perform tasks in parallel or in collaboration. Driven by the need to solve the more complex assembly line-balancing problems found in the automotive industry, this study aims to address the ALBP-HRC with the cycle time and the number of operators (humans and robots) as the primary and secondary objective, respectively. In addition to the traditional ALBP constraints, the human and robot characteristics, in terms of task times, allowing multiple humans and robots at stations, and their joint/collaborative tasks are formulated into a new mixed-integer linear programming (MILP) model. A neighborhood-search simulated annealing (SA) is proposed with customized solution representation and neighborhood search operators designed to fit into the problem characteristics. Furthermore, the proposed SA features an adaptive neighborhood selection mechanism that enables the SA to utilize its exploration history to dynamically choose appropriate neighborhood operators as the search evolves. The proposed MILP and SA are implemented on real cases taken from the automotive industry where stations are designed for HRC. The computational results over different problems show that the adaptive SA produces promising solutions compared to the MILP and other swarm intelligence algorithms, namely genetic algorithm, particle swarm optimization, and artificial bee colony. The comparisons of human/robot versus HRC settings in the case study indicate significant improvement in the productivity of the assembly line when multiple humans and robots with collaborative tasks are permissible at stations.

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  • 39.
    Nourmohammadi, Amir
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Fathi, Masood
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment. Division of Industrial Engineering and Management, Uppsala University, Sweden.
    Ng, Amos H. C.
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment. Division of Industrial Engineering and Management, Uppsala University, Sweden.
    Balancing and scheduling human-robot collaborated assembly lines with layout and objective consideration2024In: Computers & industrial engineering, ISSN 0360-8352, E-ISSN 1879-0550, Vol. 187, article id 109775Article in journal (Refereed)
    Abstract [en]

    The recent Industry 4.0 trend, followed by the technological advancement of collaborative robots, has urged many industries to shift towards new types of assembly lines with human-robot collaboration (HRC). This type of manufacturing line, in which human skill is supported by robot agility, demands an integrated balancing and scheduling of tasks and operators among the stations. This study attempts to deal with these joint problems in the straight and U-shaped assembly lines while considering different objectives, namely, the number of stations (Type-1), the cycle time (Type-2), and the cost of stations, operators, and robot energy consumption (Type-rw). The latter type often arises in the real world, where multiple types of humans and robots with different skills and energy levels can perform the assembly tasks collaboratively or in parallel at stations. Additionally, practical constraints, namely robot tool changes, zoning, and technological requirements, are considered in Type-rw. Accordingly, different mixed-integer linear programming (MILP) models for straight and U-shaped layouts are proposed with efficient lower and upper bounds for each objective. The computational results validate the efficiency of the proposed MILP model with bounded objectives while addressing an application case and different test problem sizes. In addition, the analysis of results shows that the U-shaped layout offers greater flexibility than the straight line, leading to more efficient solutions for JIT production, particularly in objective Type-2 followed by Type-rw and Type-1. Moreover, the U-shaped lines featuring a high HRC level can further enhance the achievement of desired objectives compared to the straight lines with no or limited HRC.

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  • 40.
    Nourmohammadi, Amir
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Fathi, Masood
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Ng, Amos H. C.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Choosing efficient meta-heuristics to solve the assembly line balancing problem: A landscape analysis approach2019In: Procedia CIRP, ISSN 2212-8271, E-ISSN 2212-8271, Vol. 81, p. 1248-1253Article in journal (Refereed)
    Abstract [en]

    It is widely known that the assembly line balancing problem (ALBP) is an NP-hard optimization problem. Although different meta-heuristics have been proposed for solving this problem so far, there is no convincing support that what type of algorithms can perform more efficiently than the others. Thus, using some statistical measures, the landscape of the simple ALBP is studied for the first time in the literature. The results indicate a flat landscape for the problem where the local optima are uniformly scattered over the search space. Accordingly, the efficiency of population-based algorithms in addressing the considered problem is statistically validated.

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  • 41.
    Nourmohammadi, Amir
    et al.
    University of Skövde, Virtual Engineering Research Environment. University of Skövde, School of Engineering Science.
    Fathi, Masood
    University of Skövde, Virtual Engineering Research Environment. University of Skövde, School of Engineering Science. Division of Industrial Engineering and Management, Uppsala University, Uppsala, Sverige.
    Ng, Amos H. C.
    University of Skövde, Virtual Engineering Research Environment. University of Skövde, School of Engineering Science. ision of Industrial Engineering and Management, Uppsala University, Uppsala, Sverige.
    Mahmoodi, Ehsan
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    A genetic algorithm for heterogenous human-robot collaboration assembly line balancing problems2022In: Procedia CIRP, ISSN 2212-8271, E-ISSN 2212-8271, Vol. 107, p. 1444-1448Article in journal (Refereed)
    Abstract [en]

    Originated by a real-world case study from the automotive industry, this paper attempts to address the assembly lines balancing problem with human-robot collaboration and heterogeneous operators while optimizing the cycle time. A genetic algorithm (GA) with customized parameters and features is proposed while considering the characteristics of the problem. The computational results show that the developed GA can provide the decision-makers with efficient solutions with heterogeneous humans and robots. Furthermore, the results reveal that the cycle time is highly influenced by order of the operators’ skills, particularly when a fewer number of humans and robots exist at the stations.

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  • 42.
    Nourmohammadi, Amir
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Fathi, Masood
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Ruiz Zúñiga, Enrique
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Ng, Amos H. C.
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    A Genetic Algorithm for Bi-Objective Assembly Line Balancing Problem2019In: Advances in Manufacturing Technology XXXIII: Proceedings of the 17th International Conference on Manufacturing Research, incorporating the 34th National Conference on Manufacturing Research, September 10–12, 2019, Queen’s University Belfast, UK / [ed] Yan Jin, Mark Price, Amsterdam: IOS Press, 2019, Vol. 9, p. 519-524Conference paper (Refereed)
    Abstract [en]

    Assembly line designs in manufacturing commonly face the key problem of dividing the assembly tasks among the working stations so that the efficiency of the line is optimized. This problem is known as the assembly line balancing problem which is known to be NP-hard. This study, proposes a bi-objective genetic algorithm to cope with the assembly line balancing problem where the considered objectives are the utilization of the assembly line and the workload smoothness measured as the line efficiency and the variation of workload, respectively. The performance of the proposed genetic algorithm is tested through solving a set of standard problems existing in the literature. The computational results show that the genetic algorithm is promising in providing good solutions to the assembly line balancing problem.

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  • 43.
    Nourmohammadi, Amir
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Fathi, Masood
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Zandieh, Mostafa
    Department of Industrial Management, Management and Accounting Faculty, SBU, G.C., Tehran, Iran.
    Ghobakhloo, Morteza
    Department of Industrial Engineering, Minab Higher Education Center, University of Hormozgan, Bandar Abbas, Iran / Modern Technology Development and Implementation Research Center, University of Hormozgan, Bandar Abbas, Iran.
    A water-flow like algorithm for solving U-shaped assembly line balancing problems2019In: IEEE Access, E-ISSN 2169-3536, Vol. 7, p. 129824-129833Article in journal (Refereed)
    Abstract [en]

    The problem of assigning assembly tasks to the stations arranged along a material handling device is known as assembly line balancing. This paper aims to address the U-shaped assembly line balancing problem (UALBP) which arises when a U-shaped assembly line has to be configured. It is widely known that this problem is NP-hard. Accordingly, different meta-heuristics based on a single solution (such as Simulated Annealing) or a population of solutions (such as Genetic Algorithms) have been proposed in the literature. Meanwhile, it has been argued that either of these meta-heuristics with a fixed number of solutions cannot maintain efficient search progress and thus can lead to premature convergence. Thus, this study aims at adopting a novel meta-heuristic algorithm with dynamic population sizes, namely Water Flow-like Algorithm (WFA), inspired by the behaviour of water flows in nature, to address the UALBP. The line efficiency and variation of workload are considered as the primary and the secondary objective, to be optimized, respectively. To verify the efficiency and robustness of the proposed WFA, a real case study taken from an automobile manufacturer as well as a set of standard problems are solved and the results compared with the existing approaches in the literature. The computational results demonstrate the superiority of the WFA, particularly in addressing medium to large-sized problems.

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  • 44.
    Nourmohammadi, Amir
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Ng, Amos H. C.
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment. Division of Industrial Engineering and Management, Department of Civil and Industrial Engineering, Uppsala University, Sweden.
    Fathi, Masood
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment. Division of Industrial Engineering and Management, Department of Civil and Industrial Engineering, Uppsala University, Sweden.
    Vollebregt, Janneke
    Scania Production Meppel B.V., Meppel, the Netherlands.
    Hanson, Lars
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Multi-objective optimization of mixed-model assembly lines incorporating musculoskeletal risks assessment using digital human modeling2023In: CIRP - Journal of Manufacturing Science and Technology, ISSN 1755-5817, E-ISSN 1878-0016, Vol. 47, p. 71-85Article in journal (Refereed)
    Abstract [en]

    In line with Industry 5.0, ergonomic factors have recently received more attention in balancing assembly lines to enhance the human-centric aspect. Meanwhile, today’s mass-customized trend yields manufacturers to offset the assembly lines for different product variants. Thus, this study addresses the mixed-model assembly line balancing problem (MMALBP) by considering worker posture. Digital human modeling and posture assessment technologies are utilized to assess the risks of work-related musculoskeletal disorders using a method known as rapid entire body analysis (REBA). The resulting MMALBP is formulated as a mixed-integer linear programming (MILP) model while considering three objectives: cycle time, maximum ergonomic risk of workstations, and total ergonomic risks. An enhanced non-dominated sorting genetic algorithm (E-NSGA-II) is developed by incorporating a local search procedure that generates neighborhood solutions and a multi-criteria decision-making mechanism that ensures the selection of promising solutions. The E-NSGA-II is benchmarked against Epsilon-constraint, MOGA, and NSGA-II while solving a case study and also test problems taken from the literature. The computational results show that E-NSGA-II can find promising Pareto front solutions while dominating the considered methods in terms of performance metrics. The robustness of E-NSGA-II results is evaluated through one-way ANOVA statistical tests. The analysis of results shows that a smooth distribution of time and ergonomic loads among the workstations can be achieved when all three objectives are simultaneously considered.

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  • 45.
    Rabet, Rahmat
    et al.
    Department of Industrial Engineering, Islamic Azad University Science and Research Branch, Tehran, Iran.
    Ganji, Maliheh
    Department of Industrial Engineering, Islamic Azad University Central Tehran branch, Tehran, Iran.
    Fathi, Masood
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment. Division of Industrial Engineering and Management, Department of Civil and Industrial Engineering, Uppsala, Sweden.
    A simheuristic approach towards supply chain scheduling: Integrating production, maintenance and distribution2024In: Applied Soft Computing, ISSN 1568-4946, E-ISSN 1872-9681, Vol. 153, article id 111264Article in journal (Refereed)
    Abstract [en]

    This study attempts to integrate production, maintenance, and delivery operations among supply chain members. Despite numerous studies in the field of supply chain management, researchers have often overlooked crucial aspects, such as uncertainties in demand and production. For instance, the significant impact of maintenance activities on production flow has been underrepresented in supply chain management literature. This study investigates these gaps in the context of a fertilizer producer case study, which is characterized by seasonal demand and the functional silos syndrome due to old-fashioned management approaches. This study proposes a mathematical model and two multi-objective simheuristics for the Integrated Production, Maintenance, and Distribution Scheduling Problem (IPMDSP) considering demand variation for multiple products and product delivery time-windows using a heterogeneous fleet of vehicles. The IPMDSP is solved using the ϵ-constraint method and simheuristics linking the simulation model to customized and tuned versions of Particle Swarm Optimization (MOPSO) and the Non-dominated Sorting Genetic Algorithm (NSGA-II). The optimization objectives include minimizing maintenance duration, distribution costs, and customer dissatisfaction due to delivery tardiness. The results demonstrate the superiority of the simheuristic empowered by NSGA-II over the MOPSO in solving the IPMDSP. The comparison between the performance of deterministic and stochastic approaches in addressing the problem reveals that neglecting uncertainty caused by maintenance activities can lead to an increase in optimization objectives. Furthermore, the proposed simheuristics achieved significant improvements in minimizing objectives in solving the fertilizer producer case study. 

  • 46.
    Ruiz Zúñiga, Enrique
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    García, Erik Flores
    Department of Sustainable Production Development, KTH Royal Institute of Technology, Södertälje, Sweden.
    Urenda Moris, Matías
    Division of Industrial Engineering and Management, Uppsala University, Sweden.
    Fathi, Masood
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment. Department of Sustainable Production Development, KTH Royal Institute of Technology, Södertälje, Sweden.
    Syberfeldt, Anna
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Holistic simulation-based optimisation methodology for facility layout design with consideration to production and logistics constraints2021In: Proceedings of the Institution of mechanical engineers. Part B, journal of engineering manufacture, ISSN 0954-4054, E-ISSN 2041-2975, Vol. 235, no 14, p. 2350-2361Article in journal (Refereed)
    Abstract [en]

    Facility layout design is becoming more challenging as manufacturing moves from traditionally emphasised mass production to mass customisation. The increasing demand for customised products and services is driving the need to increase flexibility and adaptability of both production processes and their material handling systems. A holistic approach for designing facility layouts with optimised flows considering production and logistics systems constraints seems to be missing in the literature. Several tools, including traditional methods, analytic hierarchy process, multiple-attribute decision making, simulation, and optimisation methods, can support such a process. Among these, simulation-based optimisation is the most promising. This paper aims to develop a facility layout design methodology supported by simulation-based optimisation while considering both production and logistics constraints. A literature review of facility layout design with simulation and optimisation and the theoretical and empirical challenges are presented. The integration of simulation-based optimisation in the proposed methodology serves to overcome the identified challenges, providing managers and stakeholders with a decision support system that handles the complex task of facility layout design.

  • 47.
    Ruiz Zúñiga, Enrique
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Urenda Moris, Matías
    Division of Industrial Engineering and Management, Uppsala University, Sweden.
    Syberfeldt, Anna
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Fathi, Masood
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Rubio-Romero, Juan Carlos
    School of Industrial Engineering, University of Malaga, Campus of Teatinos, 29071 Malaga, Spain.
    A Simulation-Based Optimization Methodology for Facility Layout Design in Manufacturing2020In: IEEE Access, E-ISSN 2169-3536, Vol. 8, p. 163818-163828Article in journal (Refereed)
    Abstract [en]

    Optimizing production systems is urgent and indispensable if companies are to cope with global competition and a move from mass production to mass customization. The urgency of this need is more obvious in old production plants with a history of modifications, expansions, and adaptations in their production facilities. It is common to find complex, intricate and inefficient systems of material and product flows as a result of poor production facility layout. Several approaches can be used to support the design of optimal facility layouts. However, there is a lack of a suitable generic methodology for designing such layouts. Additionally, there has been little focus on the data and resources required, or on how simulation and optimization can support the design of optimal facilities. To overcome these deficiencies, this paper studies the integration of simulation and optimization for the design and improvement of facility layouts taking into account production and logistics constraints. The paper includes a generic perspective and a detailed implementation. The proposed methodology is evaluated in two case studies and by drawing on the principles and tools of the functional resonance analysis method. This method analyzes the implementation order and variability of a group of processes that can lead to unwanted outcomes. The results can provide managers and other stakeholders with a methodology that adequately considers production and logistics constraints when seeking an optimized facility layout design.

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  • 48.
    Slama, Ilhem
    et al.
    LIST3N, Université de Technologie de Troyes, France.
    Arbaoui, Taha
    LIST3N, Université de Technologie de Troyes, France.
    Nourmohammadi, Amir
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Fathi, Masood
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment. Division of Industrial Engineering and Management, Uppsala University, Sweden.
    Assembly Line Balancing with Collaborative Robots Under Uncertainty of Human Processing Times2023In: 2023 9th International Conference on Control, Decision and Information Technologies (CoDIT), IEEE, 2023, p. 2649-2653Conference paper (Refereed)
    Abstract [en]

    This paper studies the assembly line balancing problem with collaborative robots in light of recent efforts to implement collaborative robots in industrial production systems under random processing time. A stochastic version with uncertain human processing time is considered for the first time. The issue is defined by the potential for simultaneous human and robot task execution at the same workpiece, either in parallel or in collaboration. We provide stochastic mixed-integer programming based on Monte Carlo sampling approach for the balancing and scheduling of collaborative robot assembly lines for this novel issue type. In order to minimise the line cost including fixed workstation operating costs and resource costs caused by exceeding cycle time, the model determines both the placement of collaborative robots at stations and the distribution of work among humans and robots.

  • 49.
    Yousefi, Milad
    et al.
    Department of Production and Transportation Engineering, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil.
    Yousefi, Moslem
    Department of Mechanical Engineering, Islamic Azad University, Roudehen Branch, Roudehen, Iran.
    Fathi, Masood
    University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment.
    Fogliatto, Flavio
    Department of Production and Transportation Engineering, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil.
    Patient visit forecasting in an emergency department using a deep neural network approach2020In: Kybernetes, ISSN 0368-492X, E-ISSN 1758-7883, Vol. 49, no 9, p. 2335-2348Article in journal (Refereed)
    Abstract [en]

    This study aims to investigate factors affecting daily demand in an emergency department (ED) and to provide a forecasting tool in a public hospital for horizons of up to 7 days.In this study, first the important factors to influence the demand in EDs were extracted from literature then the relevant factors to our study are selected. Then a deep neural network is applied for constructing a reliable predictor.Although many statistical approaches have been proposed for tackling this issue, better forecasts are viable through employing the abilities of machine learning algorithms. Results indicate that the proposed approach outperforms statistical alternatives available in the literature such as multiple linear regression (MLR), autoregressive integrated moving average (ARIMA), support vector regression (SVR), generalized linear models (GLM), generalized estimating equations (GEE), seasonal ARIMA (SARIMA) and combined ARIMA and linear regression (LR) (ARIMA-LR).We applied this study in a single ED to forecast the patient visits. Applying the same method in different EDs may give us a better understanding of the performance of the model. The same approach can be applied in any other demand forecasting after some minor modifications.To the best of our knowledge, this is the first study to propose the use of long short-term memory (LSTM) for constructing a predictor of the number of patient visits in EDs.

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