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  • 标题:An improved hierarchical genetic algorithm for collaborative optimization of manufacturing processes in metal structure manufacturing systems
  • 本地全文:下载
  • 作者:Dezhong Qi ; Sanqiang Zhang ; Mingyong Liu
  • 期刊名称:Advances in Mechanical Engineering
  • 印刷版ISSN:1687-8140
  • 电子版ISSN:1687-8140
  • 出版年度:2017
  • 卷号:9
  • 期号:3
  • DOI:10.1177/1687814017692288
  • 语种:English
  • 出版社:Sage Publications Ltd.
  • 摘要:The multi-objective optimization problem includes plate nesting, production planning, scheduling, and equipment capacity optimization in the complex manufacturing process of metal structures. For the best optimization results, a global collaborative optimization of the manufacturing system is necessary. A multi-objective optimization model for optimized nesting, optimized scheduling, dispatch optimizing, and equipment load balancing is constructed, and an improved hierarchical genetic algorithm is then developed for a better solution. A hierarchical structure of three chromosomes is designed in this algorithm. The algorithm can be used to simultaneously solve the layout selection, process sequencing, and machine selection problems. The algorithm shortens the production cycle, reduces the number of work in process, and improves equipment utilization through the application of collaborative optimization. The computational result and comparison prove that the presented approach is quite effective to address the considered problem.
  • 关键词:Metal structures; collaborative manufacturing; hierarchical genetic algorithm; cutting; collaborative optimization
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