A Novel Approach Towards Parameter Reduction Based on Bipolar Hypersoft Set and Its Application to Decision-Making

Autor: Sagvan Y. Musa, Baravan A. Asaad
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Neutrosophic Sets and Systems, Vol 55, Pp 544-556 (2023)
Druh dokumentu: article
ISSN: 2331-6055
2331-608X
DOI: 10.5281/zenodo.7847778
Popis: For a mathematical model to describe vague (uncertain) problems effectively, it must have the ability to explain the links between the objects and parameters in the problem in the most precise way. There is no suitable model that can handle such scenarios in the literature. This deficiency serves as motivation for this study. In this article, the bipolar hypersoft set (abbreviated, BHSS) is considered since the parameters and their opposite play a symmetrical role. We present a novel theoretical technique for solving decision-making problems using BHSS and investigate parameter reductions for these sets. Algorithms for parameter reduction are provided and explained with examples. The findings demonstrate that our suggested parameter reduction strategies remove unnecessary parameters and still retain the same decision-making options.
Databáze: Directory of Open Access Journals