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  • 1.
    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, The Virtual Systems Research Centre.
    A Genetic Algorithm with Multiple Populations to Reduce Fuel Consumption in Supply Chain2019In: International Journal of Transportation Engineering, ISSN 2322-259XArticle 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.

  • 2.
    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.

  • 3.
    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.

  • 4.
    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.

  • 5.
    Fathi, Masood
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    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, The Virtual Systems Research Centre.
    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, 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.

  • 6.
    Fathi, Masood
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Nourmohammadi, Amir
    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.
    Syberfeldt, Anna
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    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.

  • 7.
    Fathi, Masood
    et al.
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    Nourmohammadi, Amir
    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.
    Syberfeldt, Anna
    University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre.
    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 problem2019In: Engineering computations, ISSN 0264-4401, E-ISSN 1758-7077Article 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.
  • 8.
    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.

  • 9.
    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.

  • 10.
    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, The Virtual Systems Research Centre.
    Corporate survival in Industry 4.0 era: the enabling role of lean-digitized manufacturing2019In: Journal of Manufacturing Technology Management, ISSN 1741-038X, E-ISSN 1758-7786Article 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.

  • 11.
    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.

  • 12.
    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.

  • 13.
    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.

  • 14.
    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.

  • 15.
    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.

  • 16.
    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.
    Ruiz Zúñiga, Enrique
    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.
    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.

  • 17.
    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.
    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.

  • 18.
    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, The Virtual Systems Research Centre.
    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 approach2019In: Kybernetes, ISSN 0368-492X, E-ISSN 1758-7883Article 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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