• 论文 •    

结合性能评价的多目标价值链设计

周永华,陈禹六   

  1. 清华大学自动化系,北京100084
  • 出版日期:2004-02-15 发布日期:2004-02-25

Multi-objective Value Chain Design Combined with Performance Evaluation

ZHOU Yong-hua, CHEN Yu-liu   

  1. Dep. of Automation, Tsinghua Univ., Beijing100084, China
  • Online:2004-02-15 Published:2004-02-25

摘要: 企业间集成如供应链管理、虚拟企业、网络化制造等,都是旨在面向顾客的价值增值,减少产品或者服务的周期时间,降低成本,提高质量,以提高权益相关者的市场竞争力和运作性能,这些都需要有效的价值链设计。价值链的运作质量与价值链上节点的组织配置情况有密切关系。价值链配置质量是对价值链运作质量的预测,提出了价值链配置质量的解析描述方法,它由平均的理想配置贴近度和基于信息熵的配置均衡性两部分组成。建立了综合考虑时间、成本和质量的可量化和不可量化指标的多目标价值链优化模型,采用混合型NSGA算法,求解这类决策变量较多的多目标优化问题。计算结果表明,价值链配置质量的解析描述方法和混合型NSGA算法,对于按照经营性能需求动态设计价值链有较好的效果。

关键词: 熵, 价值链配置质量, 多目标优化, 非受支配排序遗传算法

Abstract: Inter-enterprise integration, such as supply chain management, virtual enterprise and networked manufacturing, aims at adding the value to end customers, decreasing the cycle time and cost, improving the quality of product or service, and increasing the competitive advantages in markets and operational performances of stakeholders, which requires the effective value chain design. The operational quality of value chain is closely related to the assignment of organizations in the nodes of value chain, and the assignment of quality is the prediction of operational quality of value chain. The analytical description of assignment of value chain is presented, which is composed of two parts, i.e. the average ideal assignment approximation degree and the assignment uniformity degree based on information entropy. The time-cost-quality multi-objective optimization model synthetically considering tangible and intangible factors of value chain is developed, and the mixed NSGA (Non-dominated Sorting Genetic Algorithm) is given to solve this kind of multi-objective optimization problem with lots of decision variables. At last, the computing results are demonstrated.

Key words: entropy, assignment quality of value chain, multi-objective optimization, non-dominated sorting genetic algorithm

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