计算机集成制造系统 ›› 2014, Vol. 20 ›› Issue (08): 1807-1818.DOI: 10.13196/j.cims.2014.08.baobeifang.1807.12.2014082

• 产品创新开发技术 • 上一篇    下一篇

产品定制协同制造资源优化配置

包北方1,2,杨育1+,杨涛1,薛承梦1,3,谢建中1,4   

  1. 1.重庆大学机械传动国家重点实验室
    2.南瑞集团公司天津市普迅电力信息技术有限公司
    3.贵州财经大学信息学院
    4.富士康科技集团
  • 出版日期:2014-08-31 发布日期:2014-08-31
  • 基金资助:
    国家自然科学基金资助项目(71071173);教育部人文社会科学研究西部和边疆地区资助项目(11XJC630014);重庆市科委自然科学基金计划资助项目(cstcjjA90014);贵州省软科学研究计划资助项目(黔科合体R字[2013]LKC2030)。

Resource optimal allocation in product customization collaborative manufacturing

  • Online:2014-08-31 Published:2014-08-31
  • Supported by:
    Project supported by the National Natural Science Foundation,China (No.71071173) ,the Humanity and Social Science Foundation for west border area of MOE,China (No.11XJC630014), the Natural Science Foundation of CQ CSTC,China(No.cstcjjA90014),and the Guizhou Provincial Soft Scientific Research Program,China (No.[2013]LKC2030).

摘要: 为实现产品定制协同生产模式下各种制造资源的优化选择与配置,提出产品定制协同制造资源优化配置的双层规划求解方案。在对产品定制协同制造资源配置过程进行分析的基础上,给出客户满意度及企业定制经济效益的定义和计算公式,构建了产品定制资源优化配置的双层规划数学模型|提出一种嵌入双层迭代规则的混合遗传算法对产品定制资源优化配置双层规划模型进行求解。以某5 MW风机产品客户定制加工订单为例,验证了所提资源优化配置双层规划模型的可行性及其混合遗传算法的有效性。

关键词: 资源优化配置, 客户满意度, 企业定制经济效益, 双层规划, 混合遗传算法

Abstract: To realize the optimal selection and allocation of different resources in product customization collaborative manufacturing mode,a bi-level programming solution was presented.Based on the analysis of resource allocation process in product customization collaborative manufacturing,the definition and the calculation formula of customer satisfaction and enterprise's customization economic benefits were given,and the bi-level programming mathematical model of resource optimal allocation in product customization was constructed.A hybrid genetic algorithm embedded double iteration was proposed to solve the bi-level programming model of resource optimal allocation in product customization.The effectiveness of proposed model and algorithm was verified by the example of a customized machining order of 5MW wind turbine product.

Key words: resource optimal allocation, customer satisfaction, enterprise's customization economic benefits, bi-level programming, hybrid genetic algorithm

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