基于多目标遗传算法的可调节变量产品族优化_李中凯精选.pdfVIP

42 6 浙　江　大　学　学　报() Vol.42 No.6 2008 6 Journal of Zhejiang University (Engineering Science) Jun.2008 DOI:10.3785/j.issn.1008-973X.2008.06.023 李中凯,谭建荣,冯毅雄, 魏　喆 ( CAD CG , 310027) 　:, , (NSGA-II)., NSGA-II Pareto , .NS- GA-II , . NS- GA-II , , . , One-Stage-Ps, . :;;NSGA-II;;Pareto :TH45　　　　　:A 　　　　　:1008-973X(2008)06-1015-06 Optimization of scale-based product family using multiobjective genetic algorithm LI Zhong-kai, TAN Jian-rong, FENG Yi-xiong, WEI Zhe (S tate K ey Laboratory of CAD CG, Zhej iang University , Hangzhou 310027, China) Abstract:An optimization process using nondominated sorting genetic algorithm-II(NSGA-II) as put for- ard based on the theoretical model and the optimization model of scale-based product family .Based on the mathematical model of product family design, the Pareto set for the multiobjective optimization problem as obtained using NSGA-II.An approach based on fuzzy set theory as developed to extract one of the Pareto-optimal solutions as the best compromise one.During the first stage, each product in the family as optimized independently ith NSGA-II.The design variables that sho ed small deviations ere held constant to form the product platform.In the second stage, the scaling variables of each instance product ere developed also using NSGA-II.The performance of instance product as improved on the premise that the design requirements of scale-based product family ere satisfied.The efficiency and effectiveness of the proposed method ere illustrated by the optimization design of the scale-based universal motor fami- lies and the comparison against the designs obtained from the one-stage-Ps method. Key words:scale-based product family;product platform;nondominated sorting genetic algorith