摘要
针对产品方案优化中对创新性和满意度这2项感性指标综合评估的需求,基于用户创新思想和交互式遗传算法构建了融合优化机制.通过差异化集结来评估方案的创新性,利用改进的交互评价方法产生满意度指标和用于创新性计算的参数敏感度系数;讨论了基于回避的创新性与满意度指标融合的方式,并给出了优化目标函数.优化流程分为2个独立阶段,分别由用户和设计师主导.第一阶段基于随机种群广泛获取用户的交互评价信息,并利用统计分析方法得到敏感度系数;第二阶段在设计师的主导下实施创新性与满意度融合的进化式寻优.文中基于产品外观形态优化的例进行了应用测试.
A fusion optimization mechanism, which considers the requirements for the comprehensive consideration of product＇s creativity and user＇s satisfaction, is established based on user innovation theory and interactive genetic algorithms （IGA）. Design＇s creativity is evaluated through differentiation concentration, and the sensitive factors for creativity calculation and user＇s satisfaction are generated with an improved interactive evaluation method. The paper discusses the evasive method for integrating creativity and satisfaction factors, and provides the objective functions. Optimization process is carried out in two independent phases, which are instructed by users and designers respectively. The first phase aims at collecting user＇s evaluation information, which is taken based on random generated populations. The sensitive factors for parameters are calculated in this phase. The second phase is guided by designers to find the final solutions with evolutionary method considering both creativity and satisfaction. A prototype system has been implemented and a product shape optimizing example is taken to verify the method.
出处
《计算机辅助设计与图形学学报》
EI
CSCD
北大核心
2012年第7期954-960,共7页
Journal of Computer-Aided Design & Computer Graphics
基金
国家自然科学基金(60975048
61070043)
浙江省自然科学基金(Y1111111)
上海市重点学科建设基金(Y0102)
温州市科技计划项目(G20100195)
关键词
交互式遗传算法
用户创新
产品外观优化
创新性评价
用户满意度评价
interactive genetic algorithms
user innovation
product style optimization
creativity evaluation
user satisfaction evaluation
