1.University Of Shanghai For Science And Technology;2.Tongji University
The National Natural Science Foundation of China (General Program, Key Program, Major Research Plan)
针对概率语言信息下产品服务模块双边匹配问题, 考虑匹配主体间的相互作用和影响以及决策者的心理行为, 提出了一种基于 BWM(Best-Worst Method),DEMATEL(Decision Making Trial and Evaluation Laboratory) 权重确定方法和改进 TODIM 的概率语言双边匹配方法. 首先, 通过 BWM 方法和概率语言 DEMATEL 方法来确定各匹配模块综合权重; 其次, 通过 TODIM 方法计算产品服务模块的总体优势度, 得到产品服务模块双边匹配满意度矩阵? 在此基础上, 构建以产品和服务效用达到最大的多目标优化模型, 利用线性加权法将其转为单目标模型求解, 进而得到最优匹配方案; 最后, 通过新能源汽车产品服务匹配的案例, 验证论文所提出方法的有效性和可行性, 为新能源汽车产品与服务融合发展提供新方向.
A two-sided matching method with probabilistic linguistic term sets is proposed based on BWM(Best-worst Method), DEMATEL(Decision Making Trial and Evaluation Laboratory), and TODIM, which is to solve the product service modules matching problem with probabilistic language information considering its interaction and the psychological behavior of decision makers. Firstly, the weight of modules is determined by the BWM method and DEMATEL with probabilistic linguistic term sets. Then, the total dominance degree of product service modules is calculated based on TODIM, obtaining the satisfied matrix. Furthermore, a multi-objective optimization model is constructed to maximize the utility of products and services, which is converted into a single-objective model using the linear weighting method. Finally, an example of the new energy vehicle is provided to prove the effectiveness and feasibility of the proposed method, providing a new direction for the integrated development of new energy vehicle products and services.