基于Pythagorean犹豫模糊集相似测度的多属性决策方法

摘要

针对模糊信息下的决策问题,提出了一种基于Pythagorean犹豫模糊相似性测度的多属性决策方法.首先,基于最小公倍数的原理,介绍了一种新的扩充规则用以处理Pythagorean犹豫模糊集(PHFS)之间隶属度(非隶属度)长度不一致的情况,该方法能有效地保持原始信息的信息量.其次,定义了4种Pythagore-an犹豫模糊集的相似性测度,并讨论了其相关性质,考虑到决策问题中多个属性的权重,给出了几种加权相似性测度.最后,提出了一种基于Pythagorean犹豫模糊集的TOPSIS方法用以解决多属性决策问题,并通过软件开发项目评估实例验证了该方法的可行性和有效性.%A multiple attribute decision making approach which bases on Pythagorean fuzzy similarity measure is proposed to solve decision problem under fuzzy environment. Firstly,a new method which bases on least common multiple principle is intro-duced. The method does not only solve the situation that the length of membership degrees(or non-membership degrees) is dif-ferent,but also assures the quantity of original message in Pythagorean hesitant fuzzy set(PHFS). Secondly, some similarity measure definitions based on PHFS are given,and interrelated characters are discussed. Considering weights of multiple attrib-utes in decision making problem, several weighted similarity measures are given. Finally, this paper gives a TOPSIS method based on Pythagorean hesitant fuzzy set,which is used to deal with multi-attribute decision making problem. And citing an ex-ample on software development program illustrates above methods effectiveness and feasibility.