Complex Fermatean fuzzy geometric aggregation operators and their application on group decision-making problem based on Einstein T-norm and T-conorm

IF 3.1 3区计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Soft Computing Pub Date : 2024-08-28 DOI:10.1007/s00500-024-09804-x

Khaista Rahman, Rifaqat Ali, Tarik Lamoudan

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Abstract

Complex Fermatean fuzzy set (CFF-Sets) is one of the successful extensions of complex Pythagorean fuzzy sets (CPF-Sets). The main objective of the paper is to present complex Fermatean fuzzy sets (CFF-Sets), complex Fermatean fuzzy numbers (CFFNs) and some of their basic operational laws and their corresponding aggregation operators, which can represent the time-periodic problems and two-dimensional information in a single set. We introduce various novel operators, such as complex Fermatean fuzzy Einstein weighted geometric aggregation (CFFEWGA) operator, complex Fermatean fuzzy Einstein ordered weighted geometric aggregation (CFFEOWGA) operator, complex Fermatean fuzzy Einstein hybrid geometric aggregation (CFFEHGA) operator, induced complex Fermatean fuzzy Einstein ordered weighted geometric aggregation (I-CFFEOWGA) operator, and induced complex Fermatean fuzzy Einstein hybrid geometric aggregation (I-CFFEHGA) operator along with their structure properties, such as idempotency, boundedness and monotonicity. An illustrative example related to the selection of the more suitable location for hospital is to be considered to show the effectiveness and efficiency of the novel approach.

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基于爱因斯坦 T 准则和 T 准则的复费马泰模糊几何聚合算子及其在群体决策问题中的应用

复费马提模糊集（CFF-Sets）是复毕达哥拉斯模糊集（CPF-Sets）的成功扩展之一。本文的主要目的是介绍复费马泰模糊集（CFF-Sets）、复费马泰模糊数（CFFNs）及其一些基本运算法则和相应的聚合算子，它们可以在一个集合中表示时间周期性问题和二维信息。我们引入了各种新颖的算子，如复费曼模糊爱因斯坦加权几何聚合算子（CFFEWGA）、复费曼模糊爱因斯坦有序加权几何聚合算子（CFFEOWGA）、复费曼模糊爱因斯坦混合几何聚合算子（CFFEHGA）、诱导复费马泰模糊爱因斯坦有序加权几何聚合（I-CFFEOWGA）算子和诱导复费马泰模糊爱因斯坦混合几何聚合（I-CFFEHGA）算子，以及它们的结构特性，例如幂等性、有界性和单调性。我们将考虑一个与选择更合适的医院地点有关的示例，以显示新方法的有效性和效率。

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来源期刊

Soft Computing 工程技术-计算机：跨学科应用

CiteScore

8.10

自引率

9.80%

发文量

927

审稿时长

7.3 months

期刊介绍： Soft Computing is dedicated to system solutions based on soft computing techniques. It provides rapid dissemination of important results in soft computing technologies, a fusion of research in evolutionary algorithms and genetic programming, neural science and neural net systems, fuzzy set theory and fuzzy systems, and chaos theory and chaotic systems. Soft Computing encourages the integration of soft computing techniques and tools into both everyday and advanced applications. By linking the ideas and techniques of soft computing with other disciplines, the journal serves as a unifying platform that fosters comparisons, extensions, and new applications. As a result, the journal is an international forum for all scientists and engineers engaged in research and development in this fast growing field.