包含构件成组约束的多目标产品架构模块划分

Multi-objective module division method for product architecture incorporating component grouping constraints

针对传统的基于设计结构矩阵和设计产品矩阵/模块指示矩阵的产品模块划分方法中优化解往往不符合特定构件局部成组的实际要求、粒度过大等问题,提出一种包含局部成组约束条件的多目标优化方法。设计人员根据设计结构矩阵和设计产品矩阵/模块指示矩阵的单独聚类结果以及先验知识确定所期望的特定构件局部成组方案。建立以设计结构矩阵的模块度、设计产品矩阵/模块指示矩阵的正交度和模块内聚度为优化目标、以局部成组方案为约束条件的聚类优化模型。采用改进型非支配排序遗传算法对该问题进行求解,得到Pareto解集;利用逼近理想解排序法帮助设计人员在Pareto解集中选择出合适的折衷解作为模块划分方案。以手提式吸尘器的模块划分为例,运用数值仿真手段验证了该方法的有效性和可行性。

To solve the problem of generating optimal solutions which could not satisfy the practical partial grouping requirements of special components in the traditional product-module division method based on Design Structure Matrix(DSM)and Design Product Matrix/Module Indication Matrix(DPM/MIM),and to avoid generating too coarse-grained modules,a multi-objective module division approach incorporating component grouping constraints was proposed.Desired component partial grouping schemes were built up by engineers according to results of DSM clustering and DPM/MIM clustering and other priori knowledge.A clustering optimization model with partial grouping schemes as clustering constraints was constructed.In this model,three optimization objectives were considered:the modularity quality for DSM,the reangularity and the module coherence for DPM/MIM.The elitist non-dominated sorting genetic algorithm was used to search a Pareto optimal set for this problem.Subsequently,the technique for order preference by similarity to ideal solution was utilized to help decision makers select the proper compromise solution from the Pareto front.A handheld vacuum cleaner was taken as an example to verify the effectiveness of the proposed method.