Optimizing integrated distributed flexible job-shop scheduling and customer order delivery
2025 (English)In: Journal of Industrial and Production Engineering, ISSN 2168-1015, E-ISSN 2168-1023, Vol. 42, no 4, p. 440-460Article in journal (Refereed) Published
Abstract [en]
This study addresses the Distributed Flexible Job-Shop Scheduling Problem (DFJSP) while considering the delivery of customer orders and transportation time. To tackle the problem, a mathematical model is presented, and a novel variant of the Genetic Algorithm (GA), called Time-Travel GA (TTGA), is developed. The optimization objectives include minimizing the total orders’ delivery time to the related customers, reducing transportation and production costs, reducing manufacturing pollution, and maximizing the quality of completed orders. The performance of TTGA is tested by implementing it in a real-life manufacturing setting. Additionally, TTGA results are compared with those of four other algorithms over a set of test problems. Furthermore, the solutions obtained by TTGA are compared with the optimal solutions obtained by a commercial solver for small-size problems. The results of these comparisons collectively demonstrate the promising performance of TTGA in addressing the DFJSP.
Place, publisher, year, edition, pages
Taylor & Francis Group, 2025. Vol. 42, no 4, p. 440-460
Keywords [en]
distribution, flexible job-shop, genetic algorithm, mathematical model, Multi-site manufacturing system, scheduling, Flexible manufacturing systems, Scheduling algorithms, Travel time, Customer orders, Flexible job shops, Flexible job-shop scheduling, Flexible job-shop scheduling problem, Multi-site, Performance, Time travel, Transportation time, Job shop scheduling
National Category
Computational Mathematics Transport Systems and Logistics Computer Systems
Research subject
Virtual Production Development (VPD)
Identifiers
URN: urn:nbn:se:his:diva-24800DOI: 10.1080/21681015.2024.2435847ISI: 001371249000001Scopus ID: 2-s2.0-85210938315OAI: oai:DiVA.org:his-24800DiVA, id: diva2:1922570
Note
© 2024 Chinese Institute of Industrial Engineers
Published online: 06 Dec 2024
Taylor & Francis Group an informa business
Correspondence Address: M.A. Beheshtinia; Industrial Engineering Department, Faculty of Engineering, Semnan University, Semnan, 35131-19111, Iran; email: beheshtinia@semnan.ac.ir
2024-12-192024-12-192025-09-29Bibliographically approved