• 论文 •    

基于多目标进化算法的协同设计冲突消解方法

王丽萍,江波,邱飞岳   

  1. 1.浙江工业大学 智能信息处理研究所,浙江杭州310023;2.浙江工业大学 经贸学院,浙江杭州310023;3.浙江工业大学 现代教育技术研究所,浙江杭州310012
  • 出版日期:2010-09-15 发布日期:2010-09-25

Conflict resolution method based on multi-objective evolutionary algorithms in collaborative design

WANG Li-ping, JIANG Bo, QIU Fei-yue   

  1. 1.Institute of Intelligence Information Processing, Zhejiang University of Technology, Hangzhou 310023, China;2.College of Business and Administration,Zhejiang University of Technology, Hangzhou 310023, China;3.Institute of Educational Technology,Zhejiang University of Technology, Hangzhou 310012, China
  • Online:2010-09-15 Published:2010-09-25

摘要: 针对协同设计中的目标冲突问题,提出了基于模糊集和多目标进化算法的冲突消解方法。分析了协同设计冲突产生的原因,建立了冲突问题的多目标模型;使用多目标进化算法对模型进行求解,得出符合决策者决策偏好的最优解集;利用基于模糊集理论的满意度函数对解集进行满意度排序,选取满意度最大的解作为综合最优解。以两个典型工程设计问题为应用案例进行仿真实验,利用基于决策偏好多目标粒子群算法来搜索符合决策偏好的最优方案集,并与基于多目标决策的协同设计冲突消解方法进行对比分析,结果证明了该方法的有效性。

关键词: 协同设计, 冲突消解, 多目标优化, 满意度函数

Abstract: A conflict resolution method based on fuzzy set and Multi-Objective Evolutionary Algorithms (MOEAs) was presented to solve the Goal Conflict Problem (GCP) in the collaborative design system. Reasons of GCP in collaborative design were analyzed and the multi-objective model of the GCP was established firstly. Then, the MOEAs were used to solve the proposed multi-objective model,and the optimal set according with decision preference was obtained. Finally, the Satisfaction Function (SF) based on fuzzy set theory was used to sort the solution sets, and the best SF value was regarded as the optimal relation. In the simulation experiment, two classical engineering design problems were used as application examples.Multi-Objective Particle Swarm Optimization algorithm based on Decision Preferences (DPMOPSO) was used to search the optimal solutions that in accordance with decision preferences. And the comparison was carried out with confliction resolution method based on multi-objective decision-making in collaborative design. The results demonstrated the validity of this method.

Key words: collaborative design, conflict resolution, multi-objective optimization, satisfaction function, product design

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