A New Multi-objective Job Shop Scheduling with Setup Times Using a Hybrid Genetic Algorithm
Publish Year: 1391
نوع سند: مقاله ژورنالی
زبان: English
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شناسه ملی سند علمی:
JR_IJE-26-2_003
تاریخ نمایه سازی: 17 خرداد 1393
Abstract:
This paper presents a new multi-objective job shop scheduling with sequence-dependent setup times. The objectives are to minimize the makespan and sum of the earliness and tardiness of jobs in a timewindow. Scince a job shop scheduling problem has been proved to be NP-hard in a strong, traditionalapproaches cannot reach to an optimal solution in a reasonable time. Thus, we propose an efficient multi-objective hybrid genetic algorithm (GA). We assign fitness based dominance relation and weighted aggregate in the genetic algorithm and local search, respectively.We take a variableneighborhood search algorithm as a local improving procedure in the proposed algorithm to the best individuals in the population of GA every specific number generations. To validate the efficiency of our proposed HGA, a number of test problems are solved. Its performance based on some comparison metrics is compared with a prominent multi-objective evolutionary algorithm, namely SPEA-II. The computational results show that the proposed HGA outperforms the SPEAII algorithm.
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Authors
m.b Fakhrzad
Department of Industrial Engineering, University of Yazd, Iran
a Sadeghieh
Department of Industrial Engineering, University of Yazd, Iran
l Emami
Department of Industrial Engineering, University of Yazd, Iran