基于阿基米德t-符合和t-范数的区间值对偶犹豫模糊优先聚合算子及其在多准则决策中的应用

IF 1.2 4区 计算机科学 Q4 AUTOMATION & CONTROL SYSTEMS
A. Sarkar
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引用次数: 3

摘要

多准则决策(MCDM)技术和方法已成为决策和系统工程领域的研究热点。本文的主要目的是开发区间值对偶犹豫模糊(IVDHF)环境下基于阿基米德t-符合和t-范数(At-CN&t-Ns)的多准则决策(MCDM)的优先算子。定义了一个新的评分函数,用于根据决策者施加的标准的优先级,在具有IVDHF信息的MCDM问题中查找备选方案的排名。介绍了两种聚合算子:基于at - cn&t - n的IVDHF优先加权平均(AIVDHFPWA)和加权几何(AIVDHFPWG)聚合算子。还详细研究了它们的一些理想性质。基于优先级的MCDM方法是在IVDHF信息下导出的。本文以我国某高校聘用优秀海外教师加强学历教育的MCDM问题为例进行了分析。该方法也适用于解决其他具有IVDHF信息的现实生活中的MCDM问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Interval-valued dual hesitant fuzzy prioritized aggregation operators based on Archimedean t-conorm and t-norm and their applications to multi-criteria decision making
Multi-criteria decision making (MCDM) technique and approach have been a trending topic in decision making and systems engineering to choosing the probable optimal options. The primary purpose of this article is to develop prioritized operators to multi-criteria decision making (MCDM) based on Archimedean t-conorm and t-norms (At-CN&t-Ns) under interval-valued dual hesitant fuzzy (IVDHF) environment. A new score function is defined for finding the rank of alternatives in MCDM problems with IVDHF information based on priority levels of criteria imposed by the decision maker. This paper introduces two aggregation operators: At-CN&t-N-based IVDHF prioritized weighted averaging (AIVDHFPWA), and weighted geometric (AIVDHFPWG) aggregation operators. Some of their desirable properties are also investigated in details. A methodology for prioritization-based MCDM is derived under IVDHF information. An illustrative example concerning MCDM problem about a Chinese university for appointing outstanding oversea teachers to strengthen academic education is considered. The method is also applicable for solving other real-life MCDM problems having IVDHF information.
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来源期刊
Archives of Control Sciences
Archives of Control Sciences Mathematics-Modeling and Simulation
CiteScore
2.40
自引率
33.30%
发文量
0
审稿时长
14 weeks
期刊介绍: Archives of Control Sciences welcomes for consideration papers on topics of significance in broadly understood control science and related areas, including: basic control theory, optimal control, optimization methods, control of complex systems, mathematical modeling of dynamic and control systems, expert and decision support systems and diverse methods of knowledge modelling and representing uncertainty (by stochastic, set-valued, fuzzy or rough set methods, etc.), robotics and flexible manufacturing systems. Related areas that are covered include information technology, parallel and distributed computations, neural networks and mathematical biomedicine, mathematical economics, applied game theory, financial engineering, business informatics and other similar fields.
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