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Algorithms Based on COPRAS and Aggregation Operators with New Information Measures for Possibility Intuitionistic Fuzzy Soft Decision-Making

机译:基于COPRAS和聚合运营商的算法,具有新的信息措施,用于可能性直观模糊软决策

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The objective of this paper is to present novel algorithms for solving the multiple attribute decision-making problems under the possibility intuitionistic fuzzy soft set (PIFSS) information. The prominent characteristics of the PIFSS are that it considers the membership and nonmembership degrees of each object during evaluation and their corresponding possibility degree. Keeping these features, this paper presents some new operation laws, score function, and comparison laws between the pairs of the PIFSSs. Further, we define COmplex PRoportional ASsessment (COPRAS) and weighted averaging and geometric aggregation operators to aggregate the PIFSS information into a single one. Later, we develop two algorithms based on COPRAS and aggregation operators to solve decision-making problems. In these approaches, the experts and the weights of the parameters are determined with the help of entropy and the distance measure to remove the ambiguity in the information. Finally, a numerical example is given to demonstrate the presented approaches.
机译:本文的目的是呈现用于解决可能性直觉模糊软件(PIFS)信息的多个属性决策问题的新算法。 PIFS的突出特征是它考虑了评估期间每个对象的成员和非实施度和相应的可能性程度。本文保持这些功能,介绍了一些新的操作法律,得分功能和PIFS的对之间的比较定律。此外,我们定义复杂的比例评估(COPRAS)和加权平均和几何聚合运算符,以将PIFS信息聚合到一个单个中。后来,我们基于Copras和聚合运营商开发了两种算法,以解决决策问题。在这些方法中,借助熵和距离测量来确定参数的专家和权重,以消除信息中的模糊性。最后,给出了数值例子来展示所提出的方法。

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