Applying consistent fuzzy preference relations to partnership selection

Partnership selection has been important to the formation of a virtual enterprise. Based on the fuzzy preference programming (FPP) method proposed by Mikhailov [Fuzzy analytical approach to partnership selection in formation of virtual enterprises. Omega 2002;30:393–401], this investigation presents a consistent fuzzy preference relations method to select partners. Human thoughts are full of uncertainty, so the decision-makers cannot make exact pairwise comparisons. The FPP method solves this problem using an interval value instead of Saaty's 1–9 scale. In this study, the FPP method is reviewed, and then the consistent fuzzy preference relations method is elucidated. Finally, the presented method is applied to the example addressed by Mikhailov [Fuzzy analytical approach to partnership selection in formation of virtual enterprises. Omega 2002;30:393–401]. This study reveals that the proposed method yields consistent decision rankings from only n-1$n-1$ pairwise comparisons—the same number as in Mikhailov's research. Briefly, the presented consistent fuzzy preference relations method is an easy and practical way to provide rankings of partnership in making decision.     

固定分区下随机需求IRP问题最优策略及算法

随机需求库存-路径问题(stochastic demand inventory routing problem,SDIRP)是典型的NP难题,考虑随机需求环境下供应链中库存与配送问题的协调优化,是实施供应商管理库存策略的关键所在.文章的研究基于固定分区策略(fixed partition policy,FPP),在FPP下客户被分为若干个服务区域,在同一区域中的所有客户均被同时配送.根据分区策略对配送以及库存成本的影响提出了基于修正C-W节约算法的客户分区算法,证明了各区域的最优库存策略为(s,S)形式,分区内各客户的库存策略为order-up-to形式,进而设计了求解FPP下SDIRP最优策略的算法.最后,通过数值算例验证了该算法的有效性以及FPP的适用性.