Trust modeling based on a combination of fuzzy analytic hierarchy process and fuzzy VIKOR

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

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.

An Interval-Valued Bipolar Fuzzy Linguistic VIKOR Method using Connection Numbers of SPA Theory and Its Application to Decision Support System

The plan of this research is to establish an innovative multi-attribute group decision-making (MAGDM) based on a interval-valued bipolar fuzzy set (IVBFS) by unifying“ VIseKriterijumska Optimizacija I Kompromisno Rasenje (VIKOR)” method. The VIKOR method is regarded to be a helpful MAGDM technique, particularly in circumstances where an expert is unable to properly determine his decision at the outset of the design of the scheme. The theory of set pair analysis (SPA) is a state-of-the-art uncertainty theory consisting of three variables, including “identity degree”, “discrepancy degree” and “opposite degree” of connection numbers (CNs) and a combination of many current theories dealing with vagueness in the data. Inspired by this, we are therefore making an attempt in the current research to enhance the theory of information measurement by incorporating certain metrics using CNs. In this research paper, we present the linguistic VIKOR method in the context of the CNs based metrics obtained from the interval-valued bipolar fuzzy numbers (IVBFNs). First of all, we create CNs of IVBFNs and then CN-based metrics. Secondly, we develop linguistic VIKOR method using CNs based metrics to handle an MAGDM problem under IVBF type information. The predominance and advantages of proposed approach are also highlighted. Furthermore, we demonstrate the efficiency of the extended VIKOR method by solving a numerical example, sensitivity analysis and a detailed comparison with some existing approaches.