Re-entrant flow shop scheduling problem with time windows using hybrid genetic algorithm based on auto-tuning strategy |
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| Authors: | Chettha Chamnanlor Chen-Fu Chien Mitsuo Gen |
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| Affiliation: | 1. Department of Industrial Engineering, Faculty of Engineering, Khon Kaen University, Khon Kaen, Thailand;2. Department of Industrial Engineering and Engineering Management, National Tsing Hua University, Hsinchu, Taiwan, ROC;3. Fuzzy Logic Systems Institute, Iizuka, Fukuoka, Japan |
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| Abstract: | The re-entrant flow shop scheduling problem considering time windows constraint is one of the most important problems in hard-disc drive (HDD) manufacturing systems. In order to maximise the system throughput, the problem of minimising the makespan with zero loss is considered. In this paper, evolutionary techniques are proposed to solve the complex re-entrant scheduling problem with time windows constraint in manufacturing HDD devices with lot size. This problem can be formulated as a deterministic Fm?|?fmls, rcrc, temp?|?Cmax problem. A hybrid genetic algorithm was used for constructing chromosomes by checking and repairing time window constraints, and improving chromosomes by a left-shift heuristic as a local search algorithm. An adaptive hybrid genetic algorithm was eventually developed to solve this problem by using fuzzy logic control in order to enhance the search ability of the genetic algorithm. Finally, numerical experiments were carried out to demonstrate the efficiency of the developed approaches. |
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| Keywords: | re-entrant flow shop time window hybrid genetic algorithm local search auto-tuning strategy fuzzy logic control |
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