A hybrid multi-objective genetic algorithm based on the ELECTRE method for a capacitated flexible job shop scheduling problem

被引：1
作者：
Mohamad Rohaninejad
Amirsaman Kheirkhah
Parviz Fattahi
Behdin Vahedi-Nouri
机构：
[1] Bu-Ali Sina University,Department of Industrial Engineering
来源：
The International Journal of Advanced Manufacturing Technology | 2015年 / 77卷
关键词：
Scheduling; Flexible job shop; Multi-objective genetic algorithm; ELECTRE method; Pareto optimal front;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
In this paper, a multi-objective flexible job shop scheduling problem with machines capacity constraints is studied. Minimizing the makespan and overtime costs of machines are considered as two objectives for evaluating solutions. First, a new nonlinear integer programming model is presented to formulate the problem. Inasmuch as this problem is well-known as a NP-hard problem, a hybrid meta-heuristic algorithm (CFJSP II) is developed to overcome its complexity. Regarding to the solution space of the problem, for assigning and sequencing operations, a multi-objective genetic algorithm based on the ELECTRE method is presented. Also, a powerful heuristic approach to tradeoff the objective functions is developed. Finally, the proposed algorithm is compared with some well-known multi-objective algorithms such as NSGAII, SPEA2, and VEGA. Regarding to the computational results, it is clear that the proposed algorithm has a better performance especially in the closeness of the solutions to the Pareto optimal front.
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页码：51 / 66
页数：15
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