混合数据和属性关联下合作伙伴初选群决策

Group Decision Making on Primary Partner Selection With Fuzzy Heterogeneous Data and Attribute Interdependences

合作伙伴选择的正确与否,直接影响敏捷供应链的运行,因此研究合作伙伴的选择具有重要的意义。由于不同的属性具有不同的特性,而且有的属性之间存在不同程度的关联,因此是合作伙伴选择是混合数据和属性关联下的决策问题。首先研究了如何将不同类型的属性值规范化为标准语言评价集中的模糊语言值的方法。其次采用基于最大熵原则2-可加模糊测度方法确定属性及属性集的模糊测度。应用基于关联的二元语义混合加权几何平均算子集结专家个体评价值为群体评价值,应用基于关联的二元语义加权几何平均算子集结方案各属性群体评价值为方案综合评价值。最后通过比较进一步说明了此方法的可行性和优越性。

It matters much and therefore is of great moment to the successful operations of an agile supply chain whether or not the partner selection is proper. The problem of primary partner selection is that of decision making under fuzzy heterogeneous data and attribute interdependenccs environment, since the nature of evaluated attributes varies and there exists interdependences in some of the attributes. Firstly researched into the ways how to unify the different type attribute values into the linguistic terms in the standard linguistic set, and secondly two additive fuzzy measures were used to model criteria interactions by pairs and to derive the special expressions of Marichal entropy, based on the maximum of which fuzzy measures were identified. Applied the linguistic hybrid weighted geometric averaging with interaction （LHWGAI） operator to aggregating the individual ratings of each expert, and then applied the linguistic weighted geometric averaging with interaction （LWGAI） operator to aggregating each collective attribute ratings for each alternative. Finally, by comparison were illustrated the feasibilities and advantages of the proposed approach.