Article: Balancing setup workers' load of flexible job shop scheduling using hybrid genetic algorithm with tabu search strategy Journal: International Journal of Decision Support Systems (IJDSS) 2016 Vol.2 No.1/2/3 pp.71 - 90 Abstract: This paper describes optimisation of a multi-objective flexible job shop scheduling problem (MO-FJSP) in small and medium-sized enterprises (SMEs) where widely various products are manufactured in make-to-order (MTO) mode. A genetic algorithm using tabu search strategy was applied to solve the MO-FJSP incorporating weighted tardiness, setup worker load balance, and work-in-process. From experiments using data based on real-world SME, the solutions obtained using the proposed method are compared with those obtained by conventional earliest due date (EDD), and GA using multi-island. The results confirmed the effectiveness of the proposed method. Results imply that the proposed approach is applicable not only for production scheduling but also for estimating the investment of resources such as machine and worker capacity. Inderscience Publishers - linking academia, business and industry through research

Title: Balancing setup workers' load of flexible job shop scheduling using hybrid genetic algorithm with tabu search strategy

Authors: Yasuhiko Morinaga; Masahiro Nagao; Mitsuru Sano

Addresses: Graduate School of Environmental Studies, Nagoya University, Furo-cho, Chikusa-ku, Nagoya, Aichi 464-4601, Japan ' Graduate School of Environmental Studies, Nagoya University, Furo-cho, Chikusa-ku, Nagoya, Aichi 464-4601, Japan ' Chubu University, 1200 Matsumoto-cho, Kasugai, Aichi 487-8501, Japan

Abstract: This paper describes optimisation of a multi-objective flexible job shop scheduling problem (MO-FJSP) in small and medium-sized enterprises (SMEs) where widely various products are manufactured in make-to-order (MTO) mode. A genetic algorithm using tabu search strategy was applied to solve the MO-FJSP incorporating weighted tardiness, setup worker load balance, and work-in-process. From experiments using data based on real-world SME, the solutions obtained using the proposed method are compared with those obtained by conventional earliest due date (EDD), and GA using multi-island. The results confirmed the effectiveness of the proposed method. Results imply that the proposed approach is applicable not only for production scheduling but also for estimating the investment of resources such as machine and worker capacity.

Keywords: flexible job shop scheduling problem; FJSP; load balancing; work-in-process inventory; WIP inventory; tabu search; genetic algorithms; optimisation; small and medium-sized enterprises; SMEs; machine capacity; worker capacity.

DOI: 10.1504/IJDSS.2016.081737

International Journal of Decision Support Systems, 2016 Vol.2 No.1/2/3, pp.71 - 90

Received: 06 Oct 2015
Accepted: 22 Jan 2016
Published online: 24 Jan 2017 *

Title: Balancing setup workers' load of flexible job shop scheduling using hybrid genetic algorithm with tabu search strategy

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