• 论文 •    

柔性工作车间调度问题的多目标优化方法研究

魏巍,谭建荣,冯毅雄,张蕊   

  1. 1.浙江大学 流体传动及控制国家重点实验室,浙江杭州310027;2.华晨金杯汽车有限公司,辽宁沈阳110044
  • 出版日期:2009-08-15 发布日期:2009-08-25

Multi-objective optimization method research on flexible job shop scheduling problem

WEI Wei, TAN Jian-rong, FENG Yi-xiong, ZHANG Rui   

  1. 1.State Key Laboratory of Fluid Power Transmission & Control, Zhejiang University, Hangzhou 310027, China;2.Shenyang Brilliance JINBEI Automotive Corporation Limited., Shenyang 110044, China
  • Online:2009-08-15 Published:2009-08-25

摘要: 针对各工件目标不同的多目标柔性作业车间调度问题,构建了以加工成本、加工质量及制造工期为目标函数的柔性作业车间调度多目标优化数学模型。针对传统的加权系数遗传算法不能很好地解决柔性作业车间调度多目标优化问题,提出采用改进的强度Pareto进化算法,对柔性作业车间调度问题进行多目标优化,从而得出柔性车间调度问题的Pareto综合最优解。最后,结合项目实施,以某大型空分装备企业的车间调度为例,证明了文中提出的方法能很好地解决柔性工作车间调度的多目标优化问题。

关键词: 柔性车间调度, 多目标优化, 遗传算法, 强度Pareto进化算法

Abstract: To solve the multi-objective optimization problem in flexible job shop scheduling, the multi-objective scheduling optimization model, namely the cost、quality and term, was constructed. While the traditional genetic algorithm which combined random weigh could not solve the multi-objective scheduling optimization problem commendably. An improved strength Pareto evolutionary algorithm was employed to optimize the multi-objective optimization model parallelly. As a result, the optimal schema of flexible job shop scheduling was presented in the form of Pareto optimal sets. At last, an instance related with the project in the air separation equip industry was given to prove that the proposed method could solve multi-objective optimization problem in flexible job shop scheduling effectively.

Key words: flexible job shop scheduling, multi-objective optimization, genetic algorithm, SPEA2

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