AN IMPLEMENT APPROACH FOR OPTIMIZED VARIANT DESIGN BASED ON PRODUCT GENE

摘要：

Product optimization in product design is a very essential and time-consuming process especially at the variant design stage. A research project is introduced aiming to develop quickly a variant design system capable of competition and owning market shares. According to it, a new variant design idea, with a logical product structure model, is put forward based on product gene (PG). The product gene model (PGM) and its sequential gene manipulation are established, which described an optimization model of products. Adapting to the optimization model of products, an improved artificial immune algorithm (IAIA) is adopted based on basic artificial immune algotithm (BAIA). The numerical results demonstrate the high performance of the suggested methods for structural optimization with a certain constraints. It is found that the better results are obtained in variant design.

关键词： Variant design Product gene Product optimization model Artificial immune algorithm

作者: XIU-YAN ZHAO TING-TING ZHAO XIAO-PENG WEI

作者单位: Liaoning key lab of Intelligent Information Processing, Dalian University, Dalian 116622, China

会议类型: 国际会议

会议名称: 2008 International Conference on Machine Learning and Cybernetics(2008机器学习与控制论国际会议)

会议地点: 昆明

会议语种:英文

页码: 909-914

在线出版日期: 2008-07-12（万方平台首次上网日期，不代表论文的发表时间）