中文摘要：

为有效辅助工程师将顾客需求转化为产品服务系统方案,针对其技术特征,提出一种离散粒子群优化算法（DPSO）与帕累托（Pareto）结合的配置规则提取方法.该方法包括建立产品服务系统配置规则模型及构造Pareto-DPSO算法模型.Pareto-DPSO算法基于Sobol序列的频率初始化方法及离散化粒子更新方式,将连续粒子映射到十进制离散空间;并利用Pareto进行多目标下粒子优劣性评价,以获取非支配的最优规则集.以汽车产品服务系统方案配置设计为例,经与常规多目标粒子群算法及DPSO算法对比,验证了该方法对于解决多维空间内产品服务配置规则挖掘的可行性及有效性.

英文摘要：

To assist engineers to map customer requirements into technical characteristics of product service system effectively,a kind of rule extraction method combining DPSO with Pareto was proposed.The method includes establishing the model of product service system configuration rules and constructing the model of Pareto-DPSO.In Pareto-DPSO,continuous particle was mapped into a decimal discrete space using the frequency initialization method based on Sobol sequence and the particle discrete update method;Pareto was used to obtain the optimal set of rules by evaluating multiple target functions.By comparing with OMOPSO and DPSO,the feasibility and validity of the proposed method was verified by applying in the example of automotive product service system configuration design.