Hybrid flow shop scheduling with parallel batching |
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| Authors: | Mohammad Reza Amin-Naseri Mohammad Ali Beheshti-Nia |
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| Institution: | 1. Department of Industrial Engineering and Management, National Taipei University of Technology, Taipei, Taiwan, ROC;2. Department of Information Management, Chang Gung University, Taoyuan, Taiwan, ROC;3. Department of Neurology, Linkou Chang Gung Memorial Hospital, Taoyuan, Taiwan, ROC;4. Department of Industrial Engineering and Management, Ming Chi University of Technology, Taipei, Taiwan, ROC;1. State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, Hunan University, Changsha 410082, China;2. School of Electrical Engineering and Computing, The University of Newcastle, Callaghan NSW 2308, Australia |
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| Abstract: | In this research the problem of parallel batch scheduling in a hybrid flow shop environment with minimizing Cmax is studied. In parallel batching it is assumed that machines in some stages are able to process a number of operations simultaneously. Since the problem is NP-hard, three heuristic algorithms are developed to give near optimal solutions. Since this problem has not been studied previously, therefore, a lower bound is developed for evaluating the performance of the proposed heuristics. Several test problems have been solved using these heuristics and results compared. To further enhance the solution quality, a three dimensional genetic algorithm (3DGA) is also developed. Several test problems have been solved using 3DGA and the results indicate its superiority to the other heuristics. |
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