VIKOR method for MCDM based on bipolar fuzzy soft β-covering based bipolar fuzzy rough set model and its application to site selection of solar power plant

Article type: Research Article

Authors: Tufail, Faiza^{; *} | Shabir, Muhammad

Affiliations: Quaid-i-Azam University, Islamabad, Pakistan

Correspondence: [*] Corresponding author. Faiza Tufail, Quaid-i-Azam University, Islamabad, Pakistan. E-mail: [email protected].

Abstract: Bipolarity indicates the positive and negative aspects of a particular problem. The concept behind the bipolarity is that a huge range of human decision analysis is involved in bipolar subjective thoughts. The VIKOR (Vlse Kriterijumska Optimizacija Kompromisno Resenje) which means multicriteria optimization and compromise solution, has already become a quite popular multi-criteria decision making tool for its computational simplicity and solution accuracy. In this article, we propose a hybrid model for multi-criteria decision-making (MCDM) based on bipolar fuzzy soft β-covering based bipolar fuzzy rough sets using VIKOR technique. It consists of a suitable redesign of the VIKOR approach so that it can use information with bipolar configurations. This method focuses on selecting and ranking from a set of feasible alternatives, and determines compromise solution for a problem with conflicting criteria to help the decision maker in reaching a final course of action. It determines the compromise ranking list based on the particular measure of closeness to the ideal solution. For illustration, the proposed technique is applied to a decision-making problems, namely, the selection of site for renewable energy project (solar power plant). A comparison of this method with another aggregation operator method and with the existing decision making algorithm Fuzzy VIKOR is also presented.

Keywords: Bipolar fuzzy soft β-neighborhood, bipolar fuzzy soft complementry β-neighborhood, bipolar fuzzy soft β-covering, bipolar fuzzy soft β-covering based bipolar fuzzy rough set, decision-making application

DOI: 10.3233/JIFS-211223

Journal: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 3, pp. 1835-1857, 2022