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A simulated annealing for hybrid flow shop scheduling with multiprocessor tasks to minimize makespan

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Abstract

This paper studies a hybrid flow shop scheduling problem (hybrid FSSP) with multiprocessor tasks, in which a set of independent jobs with distinct processor requirements and processing times must be processed in a k-stage flow shop to minimize the makespan criterion. This problem is known to be strongly nondeterministic polynomial time (NP)-hard, thus providing a challenging area for meta-heuristic approaches. This paper develops a simulated annealing (SA) algorithm in which three decode methods (list scheduling, permutation scheduling, and first-fit method) are used to obtain the objective function value for the problem. Additionally, a new neighborhood mechanism is combined with the proposed SA for generating neighbor solutions. The proposed SA is tested on two benchmark problems from the literature. The results show that the proposed SA is an efficient approach in solving hybrid FSSP with multiprocessor tasks, especially for large problems.

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Authors and Affiliations

  1. Department of Management and Information Technology, Vanung University, Jung-Li, Tao Yuan, Taiwan, Republic of China

    Hui-Mei Wang & Ful-Chiang Wu

  2. Department of Industrial Engineering and Management, Ching Yun University, Jung-Li, Tao Yuan, Taiwan, Republic of China

    Fuh-Der Chou

Authors
  1. Hui-Mei Wang
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  2. Fuh-Der Chou
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  3. Ful-Chiang Wu
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Correspondence to Fuh-Der Chou.

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Wang, HM., Chou, FD. & Wu, FC. A simulated annealing for hybrid flow shop scheduling with multiprocessor tasks to minimize makespan. Int J Adv Manuf Technol 53, 761–776 (2011). https://doi.org/10.1007/s00170-010-2868-z

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  • DOI: https://doi.org/10.1007/s00170-010-2868-z

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