Computer Engineering and Applications ›› 2009, Vol. 45 ›› Issue (15): 223-225.DOI: 10.3778/j.issn.1002-8331.2009.15.065

• 工程与应用 • Previous Articles     Next Articles

Multi-objective optimization search for flexible job shop scheduling problem

LIANG Di1,TAO Ze2   

  1. 1.School of Mechanical Engineering,Shenyang University,Shenyang 110044,China
    2.School of Mechanical Engineering,Shenyang Science & Technology University,Shenyang 110168,China
  • Received:2008-03-26 Revised:2008-05-23 Online:2009-05-21 Published:2009-05-21
  • Contact: LIANG Di

多目标柔性作业调度的优化研究

梁 迪1,陶 泽2   

  1. 1.沈阳大学 机械工程学院 工业工程系,沈阳 110044
    2.沈阳理工大学 机械工程学院,沈阳 110168
  • 通讯作者: 梁 迪

Abstract: A hybrid algorithm is proposed to solve scheduling problem in flexible production environment,where time,cost and equipment utilization rate are all concerned.Firstly,the scheduling model is built.The scheduling precedence is determined by the representation based operation.Objective dimensions can be unified by standardization principle.Secondly,AHP application is adopted to translate multi-objective into single objective problem.In order to avoid the premature convergence of simple GA,it combines the advantage of global search ability of GA with the self-adaptive merit of Tabu Search(TS).The result of the test shows that this method is feasible and efficient.

Key words: multi-objective optimization, flexible job shop scheduling, hybrid genetic-tabu search algorithm

摘要: 针对以生产周期、生产成本、设备利用率为目标的柔性作业调度问题,基于混合遗传算法提出了一种新的优化求解方法。首先建立了该类问题的调度模型,基于工序编码的染色体决定了工序调度的优先级;利用无量纲的标准化处理方法统一目标量纲;然后,利用层次分析法将多目标问题转化为单目标问题,同时为了保证算法的收敛性,在基本遗传算法框架的基础上集成了禁忌搜索算法,从而延缓或避免了早熟收敛的发生。最后通过实验仿真,证明提出的方法可以有效解决该类多目标柔性作业调度问题。

关键词: 多目标优化, 柔性作业调度, 混合遗传算法