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中国管理科学 ›› 2019, Vol. 27 ›› Issue (3): 198-205.doi: 10.16381/j.cnki.issn1003-207x.2019.03.020

• 论文 • 上一篇    下一篇

基于混合加权距离的毕达哥拉斯模糊TOPSIS多属性决策方法研究

曾守桢1,2, 穆志民3   

  1. 1. 宁波大学商学院, 浙江 宁波 315211;
    2. 复旦大学管理学院, 上海 200433;
    3. 天津农学院基础科学学院, 天津 300384
  • 收稿日期:2017-08-24 修回日期:2018-05-22 出版日期:2019-03-20 发布日期:2019-04-28
  • 通讯作者: 曾守桢(1981-),男(汉族),江西吉安人,宁波大学商学院副教授,复旦大学管理学院博士后,研究方向:综合评价与决策分析,E-mail:zszzxl@163.com. E-mail:zszzxl@163.com
  • 基金资助:

    国家社科基金资助项目(18BTJ027)

A Method Based on Hybrid Weighted Distance for Pythagorean Fuzzy TOPSIS Multiple-attribute Decision Making

ZENG Shou-zhen1,2, MU Zhi-min3   

  1. 1. School of Business, Ningbo University, Ningbo 315211, China;
    2. School of Management, Fudan University, Shanghai 200433, china;
    3. School of Basic Science, Tianjin Agricultural University, Tianjin 300384, China
  • Received:2017-08-24 Revised:2018-05-22 Online:2019-03-20 Published:2019-04-28

摘要: 针对决策信息为毕达哥拉斯模糊集的多属性决策问题,提出了一种基于混合加权测度的TOPSIS决策方法。在分析了现有距离测度方法不足的基础上,首先给出了一种新的毕达哥拉斯模糊距离测度——毕达哥拉斯模糊有序加权距离(PFOWD),并研究了该测度权重的确定方法;在PFOWD基础上,进一步提出了毕达哥拉斯模糊混合加权距离(PFHWD),同时探讨了其特征和与现有毕达哥拉斯模糊测度的关系;最后提出了一种基于PFHWD测度的毕达哥拉斯模糊TOPSIS多属性方法,并用实例验证了方法的有效性和可行性。

关键词: 毕达哥拉斯模糊集, 距离测度, 混合加权, 多属性决策, TOPSIS

Abstract: The aim of this paper is to present a technique based on the hybrid weighted distance (PFHWD) measure for Pythagorean fuzzy TOPSIS model. Firstly, the inadequacies for the existing Pythagorean fuzzy distance measures are analyzed in detail. Then, two new distance measures, namely the Pythagorean fuzzy ordered weighted distance measure and the PFHWD measure are presented to enhance Pythagorean fuzzy theory, some of their advantages are also explored. Furthermore, based on the proposed measures, a modified TOPSIS termed the PFHWD-TOPSIS, is developed for Pythagorean fuzzy multiple attribute decision making problems. Moreover, a revised relative coefficient is proposed to rank the potential alternatives. Finally, a numerical example concerning the service quality of domestic airlines is introduced to demonstrate the effectiveness of the developed model. The research of this paper contributes to enrich the theory and application of Pythagorean fuzzy set.

Key words: Pythagorean fuzzy set, distance measure, hybrid aggregation, multiple-attribute decision making, TOPSIS

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