运筹与管理 ›› 2017, Vol. 26 ›› Issue (1): 1-7.DOI: 10.12005/orms.2017.0001

• 理论分析与方法探讨 •    下一篇

集团分布式制造模式下生产调配优化模型研究及算法设计

刘洪伟, 苑东平, 郑飞   

  1. 天津大学管理与经济学部,天津300072
  • 收稿日期:2015-01-27 出版日期:2017-01-20
  • 作者简介:刘洪伟(1971-),男,黑龙江齐齐哈尔市人,副教授,博士,主要研究方向为工业工程理论及应用,生产与服务调度等;苑东平(1990-),女,河北廊坊人,硕士,研究方向为生产与服务调度。
  • 基金资助:
    国家基础性科技工作专项(2013IM30600);天津大学自主创新基金(2013XS-0056)

Optimization of Production Allocation and Algorithm Design Basedon Group Distributed Manufacturing

LIU Hong-wei, YUAN Dong-ping, ZHENG Fei   

  1. Department of Management and Economic, Tianjin University, Tianjin 300072, China
  • Received:2015-01-27 Online:2017-01-20

摘要: 基于分布式概念的集团分布式制造生产管理模式在市场中占据着越来越重要的地位,此种运营模式由制造型企业向服务型企业蔓延的趋势也越来越明显,然而针对这一具有自身特点的集团分布式概念下的生产管理模型的调度研究却很少。研究针对此生产管理模式下集团级的生产调配问题建立数学模型,综合考虑客户订单的分散情况、各分厂日生产能力限制和产品品种多样性的特点,采用改进的遗传算法求解该模型,提出一种基于订单和工厂的两段式非负整数染色体编码方法,保证了生产能力约束和订单约束,采用PMX交叉算法避免不合法染色体的出现。选取W集团一定计划期内的客户订单数据进行实例分析,验证了该生产调配模型和算法的有效性。

关键词: 集团分布式制造, 集团级, 生产调配模型, 遗传算法

Abstract: The mode of Group Distributed Manufacturing production management based on the distributed concept has become more and more important in present market, and the trend of this operation mode changing from manufacturing enterprise to the service-oriented businesses is increasingly conspicuous. However, there exists little special scheduling research about this production management mode. Therefore, in this study a mathematical model for the production allocation problem in Group level is established, which takes the dispersion of customer orders and the limitations on factory production capacity and species diversity of production into consideration. Then, the genetic algorithm is applied to solve this problem and put forward a new two-stage and non-negative integer chromosome coding method based on the order and factory to ensure the production capacity and order constraints. The PMX cross algorithm avoids the production of illegitimate chromosome. Besides, a period of order data coming from W Group Company is analyzed to justify the validity of the model and the algorithm.

Key words: Group Distributed Manufacturing, Group level, production allocation model, genetic algorithm

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