A Novel Approach on Decision Support System Based on the Aczel-Alsina Aggregation Operators and Their Applications to Supplier Selection Problems

Author:

Wang Yong-Long1,Bonyah Ebenezer2ORCID,Khayyat Mashael3,Ahmad Zubair45,Shakeel Muhammad6,Khan Waris6ORCID

Affiliation:

1. Institute for Modern Economics and Management, Zhejiang Yuexiu University, Shaoxing 312000, China

2. Department of Mathematics Education, Akenten Appiah Menka University of Skills Training and Entrepreneurial Development, (Kumasi Campus), Ghana

3. Department of Information Systems and Technology, College of Computer Science and Engineering, University of Jeddah, Jeddah 21959, Saudi Arabia

4. Unit of Bee Research and Honey Production, Faculty of Science, King Khalid University, P.O. Box 9004, Abha 61413, Saudi Arabia

5. Applied College, Mahala Campus, King Khalid University, P.O. Box 9004, Abha 61413, Saudi Arabia

6. Department of Mathematics & Statistics, Hazara University Mansehra, 21120 KP, Pakistan

Abstract

Induced aggregation operators are more suitable for aggregating the individual preference relations into a collective fuzzy preference relation. Therefore, in this paper, we introduce the notion of some new types of induced aggregation operators, based on the Aczel-Alsina operations. We construct some induced interval-valued intuitionistic trapezoidal fuzzy Aczel-Alsina ordered weighted averaging/geometric (I-IVITrFAAOWA/G) operator, induced interval-valued intuitionistic trapezoidal fuzzy Aczel-Alsina hybrid averaging/geometric (I-IVITrFAAHA/G) operator. Moreover, some dominant properties of these developed operators are studied in detail. Based on these proposed approaches, a model is a build up for multicriteria decision making (MCDM), and their stepwise algorithm is being presented. Finally, in utilizing the developed approach, an illustrative example is solved with the help of proposed operators. In the end, we utilize an applicable example for supplier selection to prove the proposed methods and compare the result with existing methods, which shows the superiority, competence, and ability of the developed model.

Funder

King Khalid University

Publisher

Hindawi Limited

Subject

Analysis

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