Open Access

ARTICLE

Aczel-Alsina Weighted Aggregation Operators of Simplified Neutrosophic Numbers and Its Application in Multiple Attribute Decision Making

Rui Yong^1,2,*, Jun Ye^1,2, Shigui Du^1,2, Aqin Zhu¹, Yingying Zhang¹

1 Rock Mechanics Institute, Ningbo University, Ningbo, 315211, China
2 School of Civil and Environmental Engineering, Ningbo University, Ningbo, 315211, China

* Corresponding Author: Rui Yong. Email:

(This article belongs to this Special Issue: Extension, Modeling and Applications of Fuzzy Set Theory in Engineering and Science)

Computer Modeling in Engineering & Sciences 2022, 132(2), 569-584. https://doi.org/10.32604/cmes.2022.019509

Received 27 September 2021; Accepted 04 January 2022; Issue published 15 June 2022

Abstract

The simplified neutrosophic number (SNN) can represent uncertain, imprecise, incomplete, and inconsistent information that exists in scientific, technological, and engineering fields. Hence, it is a useful tool for describing truth, falsity, and indeterminacy information in multiple attribute decision-making (MADM) problems. To suit decision makers’ preference selection, the operational flexibility of aggregation operators shows its importance in dealing with the flexible decision-making problems in the SNN environment. To solve this problem, this paper develops the Aczel-Alsina aggregation operators of SNNs for MADM problems in view of the Aczel-Alsina operational flexibility. First, we define the Aczel-Alsina operations of SNNs. Then, the Aczel-Alsina aggregation operators of SNNs are presented based on the defined Aczel-Alsina operations of SNNs. Next, a MADM method is established using the proposed aggregation operators under the SNN environment. Lastly, an illustrative example about slope treatment scheme choices is provided to indicate the practicality and efficiency of the established method. By comparison with the existing relative MADM methods, the results show that the established MADM method can overcome the insufficiency of decision flexibility in the existing MADM methods and demonstrate the metric of flexible decision-making.

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Keywords

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