China Mechanical Engineering

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Two-stage Hybrid Algorithm for Integrated Process Planning and Scheduling Problems

WEN Xiaoyu;LUO Guofu;LI Hao;XIAO Yanqiu;QIAO Dongping   

  1. Henan Key Laboratory of Intelligent Manufacturing of Mechanical Equipment,Zhengzhou University of Light Industry,Zhengzhou,450002
  • Online:2018-11-25 Published:2018-11-27

[工艺规划与装配线平衡]两阶段混合算法求解集成工艺规划与调度问题

文笑雨;罗国富;李浩;肖艳秋;乔东平   

  1. 郑州轻工业学院河南省机械装备智能制造重点实验室,郑州,450002
  • 基金资助:
    河南省产学研合作计划资助项目(172107000019);
    国家自然科学基金资助项目(51775517);
    河南省高等学校重点科研项目(15A460037);
    郑州轻工业学院博士科研基金资助项目(2014BSJJ0023)

Abstract: A two-stage hybrid algorithm was designed for solving integrated process planning and scheduling problems. In process planning stage,genetic algorithm was utilized to generate alternative near-optimal process plan sets for each job. The alternative near-optimal process plan sets were used to input special process plans of jobs to job shop scheduling stage dynamically.In job shop scheduling processes,honey bees mating optimization algorithm was employed for searching the optimal solution effectively. Queens mating flight processes were designed to guarantee the global search capability of the proposed algorithm,while workers were constructed as local search strategies to improve the broods  based on different neighborhood structures. Benchmark instances were used to evaluate the performance of the proposed algorithm. The comparisons with other algorithms were also presented,which verified the effectiveness of the proposed method.

Key words: integrated process planning and scheduling, genetic algorithm, honey bees mating optimization, local search

摘要: 提出了求解集成式工艺规划与车间调度问题的两阶段混合算法。在工艺规划阶段,使用遗传算法为每个工件生成可选的近优工艺路线集,动态地为车间调度阶段输入已确定的工艺路线;在车间调度阶段,使用蜜蜂交配优化算法快速寻优,设计了蜂王婚飞的流程以保证算法的全局搜索能力,构建了基于不同邻域结构的工蜂培育幼蜂局部搜索策略。使用基准测试集对提出的方法进行验证,并与现有算法进行对比,计算结果证明了提出方法的有效性。

关键词: 集成式工艺规划与车间调度, 遗传算法, 蜜蜂交配优化, 局部搜索

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