Li Feng, Xie Jialiang, Lin Mingwei
School of Science, Jimei University, Xiamen, 361021 Fujian China.
College of Computer and Cyber Security, Fujian Normal University, Fuzhou, 350117 Fujian China.
Complex Intell Systems. 2023;9(1):51-63. doi: 10.1007/s40747-022-00778-7. Epub 2022 Jun 17.
This paper proposes a novel fuzzy multi-criteria decision-making method based on an improved score function of connection numbers and Choquet integral under interval-valued Pythagorean fuzzy environment. To do so, we first introduce a method to convert interval-valued Pythagorean fuzzy numbers into connection numbers based on the set pair analysis theory. Then an improved score function of connection numbers is proposed to make the ranking order of connection numbers more in line with reality in multi-criteria decision-making process. In addition, some properties of the proposed score function of connection numbers and some examples have been given to illustrate the advantages of conversion method proposed in the paper. Then, considering interactions among different criteria, we propose a fuzzy multi-criteria decision-making approach based on set pair analysis and Choquet integral under interval-valued Pythagorean fuzzy environment. Finally, a case of online learning satisfaction survey and a brief comparative analysis with other existing approaches are studied to show that the proposed method is simple,convenient and easy to implement. Comparing with previous studies, the method in this paper, from a new perspective, effectively deals with multi-criteria decision-making problems that the alternatives cannot be reasonably ranked in the decision-making process under interval-valued Pythagorean fuzzy environment.
本文提出了一种基于区间值毕达哥拉斯模糊环境下改进的联系数得分函数和Choquet积分的新型模糊多准则决策方法。为此,我们首先基于集对分析理论介绍一种将区间值毕达哥拉斯模糊数转换为联系数的方法。然后提出一种改进的联系数得分函数,使联系数的排序顺序在多准则决策过程中更符合实际。此外,给出了所提出的联系数得分函数的一些性质和一些例子,以说明本文提出的转换方法的优点。接着,考虑不同准则之间的相互作用,我们提出了一种基于区间值毕达哥拉斯模糊环境下集对分析和Choquet积分的模糊多准则决策方法。最后,研究了一个在线学习满意度调查案例,并与其他现有方法进行了简要的比较分析,结果表明所提出的方法简单、方便且易于实现。与以往的研究相比,本文的方法从一个新的角度有效地处理了区间值毕达哥拉斯模糊环境下决策过程中备选方案无法合理排序的多准则决策问题。