一种基于残缺信息的多准则区间直觉模糊决策方法

An approach to multicriteria decision-making based on interval-valued intuitive fuzzy set with incomplete information

提出一种权重系数存在残缺信息的多准则区间直觉模糊集的排序算法。该方法通过逻辑集成得到各方案的区间直觉模糊集,计算各种方案的区间直觉模糊数的Hamming距离,并建立非线性规划模型,利用粒子群算法求解所得的优化模型,得出最优准则的权重系数。然后通过比较区间直觉模糊集与优级方案及次级方案的距离来进行最优排序。最后利用实例对方法的有效性和可行性进行了说明。

A multicriteria ranking method was proposed in which the information on the criteria＇s weights was incomplete and the criteria＇s value was interval intuitive fuzzy set. The interval-valued intuitive fuzzy set of each program was aggregated through logical algorithms. The Hamming distance of each program was computed and nonlinear programming model was established. By using particle swarm optimization algorithms, the optional criteria weights were gained. And ranking was performed through the comparison of the distances between interval-valued intuitive fuzzy set and superior program ＆ inferior program alternative, Eventually, a practical example was provided to illustrate the validity and feasibility of this method.