• 论文 •    

设施能力可扩展的制造/再制造物流网络多周期优化设计

狄卫民,胡培   

  1. 1.郑州大学 管理工程系,河南郑州450001;2.西南交通大学 经济管理学院,四川成都610031
  • 出版日期:2009-07-15 发布日期:2009-07-25

Multi-period optimal design for manufacturing/remanufacturing logistics network considering expandable facility capacities

DI Wei-min, HU Pei   

  1. 1.Department of Management Engineering, Zhengzhou University, Zhengzhou 450001, China;2.School of Economics and Management, Southwest Jiaotong University, Chengdu 610031, China
  • Online:2009-07-15 Published:2009-07-25

摘要: 为提高制造/再制造物流管理绩效,提出了合理设计制造/再制造闭环物流网络结构的方法。考虑到物流系统不同时间段设计参数的差异、资金的时间价值和物流设施的分期建设等因素,建立了设施能力可扩展的物流网络多周期优化设计的混合整数非线性规划模型。利用该模型可以确定制造/再制造混合系统中每个周期需要新建的设施位置及数量、需要扩建的设施位置及数量、扩建设施需要扩建的标准系列数量、设施运营时需要增开的标准系列数量,以及相应物流量等,同时还可以获得计划期内的系统最小总费用。为快速有效地得到设计结果,给出了求解模型的混合遗传算法,介绍了算法的实现步骤。最后通过算例,验证了模型及其算法的有效性。

关键词: 再制造, 物流网络, 模型, 混合遗传算法, 多周期优化设计

Abstract: To improve logistics management performance of manufacturing/remanufacturing systems, an appropriate design approach for closed-loop logistics network structrues was proposed. By considering design parameters'differences between inter-related time periods, capital's time value and logistics facility construction by stages, a Mixed Integer Non-Linear Programming (MINLP) model was developed for the optimal design of the logistics network considering expandable facility capacities. With the help of the model, the following items in the hybrid systems and for different periods could be determined, such as building or rebuilding locations and numbers for various sort of facilities, the extending standard cell numbers at rebuilding locations, the opening standard cell numbers for capacity enlarging at operation facilities and the logistics quantities between the corresponding facilities, also the minimum total fees of the logistics systems in planning horizon could be obtained simultaneously. To acquire design results rapidly and effectively, a hybrid genetic algorithm for MINLP model was presented, and its realization steps were introduced. Finally, effectiveness of MINLP model and its algorithm was verified by an example.

Key words: remanufacturing, logistics network, models, hybrid genetic algorithm, multi-period optimal design

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