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EXTENSION OF THE TOPSIS METHOD BASED ON PROSPECT THEORY AND TRAPEZOIDAL INTUITIONISTIC FUZZY NUMBERS FOR GROUP DECISION MAKING

ISSN号：1004-3756
期刊名称：《系统科学与系统工程学报：英文版》
时间：0
分类：O225[理学—运筹学与控制论;理学—数学] X823[环境科学与工程—环境工程]
作者机构：[1]School of Business, Central South University, Changsha, 410083, China
相关基金：This work was partly supported by the National Natural Sciences Foundation of China （No. 71221061）, China Postdoctoral Science Foundation （No. 2014M552169） and Central South University Business Management Postdoctoral Research Station. Acknowledgments The authors wish to express their sincerest thanks to the editors and anonymous referees for their valuable comments and advice.

作者： Xihua LI Xiaohong CHEN[1]

关键词： TOPSIS法, 群体决策, 模糊数, 梯形, 直觉, TOPSIS方法, 指标权重, 模糊环境, TOPSIS, trapezoidal intuitionistic fuzzy numbers, prospect theory, group decision making, distance measures

中文摘要：

就制造者在无常下面冒险心理因素和信息歧义的决定而言，新奇 TOPSIS 基于前景理论(磅)和 trapezoidal intuitionistic ，为组决策的模糊数字( TrIFNs )被调查，在哪个标准价值和标准重量拿 TrIFNs 的形式，并且决定制造者的重量是未知的。第一，为 TrIFNs 的距离措施被用来在 trapezoidal intuitionistic 下面导致值功能模糊环境。第二，距离措施的概念和 trapezoidal intuitionistic 模糊加权的平均操作员被采用导致决定制造者的重量，因此，决定制造者选择能被聚集。然后，基于磅的分离措施和相对亲密系数被定义并且为在 trapezoidal intuitionistic 下面评价选择的一个算法模糊环境被建议。最后，一个数字例子进一步说明建议 TOPSIS 方法的实物和有效性。

英文摘要：

Considering the decision maker＇s risk psychological factors and information ambiguity under uncertainty, a novel TOPSIS based on prospect theory （PT） and trapezoidal intuitionistic fuzzy numbers （YrIFNs） for group decision making is investigated, in which the criteria values and the criteria weights take the form of TrIFNs, and weights of decision makers are unknown. Firstly, distance measures for TrIFNs are used to induce value function under trapezoidal intuitionistic fuzzy environment. Secondly, the concepts of distance measures and trapezoidal intuitionistie fuzzy weighted averaging operator are employed to induce the weights of decision makers and thus the decision makers＇ options can be aggregated. Then the PT-based separation measures and relative closeness coefficient are defined and an algorithm for ranking alternatives under trapezoidal intuitionistic fuzzy environment is proposed. Finally, a numerical example further illustrates the practicality and effectiveness of the proposed TOPSIS method.