《计算机应用研究》|Application Research of Computers

基于混合人工蜂群算法的多目标柔性作业车间调度问题研究

Study on multi-objective flexible Job-Shop scheduling problem based on hybrid artificial bee colony algorithm

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作者 孟冠军,杨大春,陶细佩
机构 合肥工业大学 机械工程学院,合肥 230009
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文章编号 1001-3695(2019)04-003-0972-03
DOI 10.19734/j.issn.1001-3695.2017.11.0993
摘要 传统的优化算法在求解面对多目标柔性作业车间调度时,往往求解效率低且难以获得最优解。为了求解多目标柔性作业车间调度问题,设计了混合人工蜂群算法。种群的初始化采用了多种方法相结合的策略。在人工蜂群算法的不同阶段采用不同的搜索机制,在雇佣蜂阶段采用开发搜索,针对跟随蜂阶段蜜蜂跟随的对象的优秀解进行小幅度的更新,从而提高了搜索的表现。禁忌搜索与改进的人工蜂群算法相结合,有效提升了获得最优解的概率。通过相关文献中的标准实例对设计的混合人工蜂群算法进行一系列求解测试,实验的结果有效说明了算法在求解柔性作业车间调度问题时效果显著。通过求解结果对比表明人工蜂群算法的高效性和优越性。
关键词 计算机应用; 柔性作业车间调度; 人工蜂群算法; 多目标优化; 禁忌搜索
基金项目 马鞍山市科技计划资助项目
本文URL http://www.arocmag.com/article/01-2019-04-003.html
英文标题 Study on multi-objective flexible Job-Shop scheduling problem based on hybrid artificial bee colony algorithm
作者英文名 Meng Guanjun, Yang Dachun, Tao Xipei
机构英文名 School of Mechanical Engineering,Hefei University of Technology,Hefei 230009,China
英文摘要 When solving multi-objective flexible Job-Shop scheduling problem, the traditional optimization algorithms were often inefficient and difficult to obtain the optimal solution. In order to solve the multi-objective flexible Job-Shop scheduling problem, this paper designed a hybrid artificial bee colony algorithm. The method in population initialization phase was combination of several strategies. Different search mechanisms were employed at different stages of the artificial bee colony algorithm: adopted the traditional exploit search in the employed bee phase, and updated objects of bees following with little range in onlooker bee phase. The combination of tabu search and improved artificial bee colony algorithm effectively improved the probability of obtaining the optimal solution. The paper tested hybrid artificial bee colony algorithm through the Kacem instances. The results show that the hybrid artificial bee colony algorithm is efficient in solving flexible Job-Shop scheduling problem. The results indicate the efficiency and superiority of artificial bee colony algorithm.
英文关键词 computer application; flexible Job-Shop scheduling problem; artificial bee colony algorithm; multi-objective optimization; tabu search
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收稿日期 2017/11/4
修回日期 2017/12/8
页码 972-974,979
中图分类号 TP399
文献标志码 A