Membership function

About: Membership function is a research topic. Over the lifetime, 15795 publications have been published within this topic receiving 418366 citations.

Multiattribute Decision Making Based on Interval-Valued Intuitionistic Fuzzy Sets, PSO Techniques, and Evidential Reasoning Methodology

Abstract: In this paper, we propose a new multiattribute decision making method based on interval-valued intuitionistic fuzzy sets, particle swarm optimization (PSO) techniques, and the evidential reasoning methodology. The proposed method uses the evidential reasoning methodology to construct objective functions of the programming models and uses PSO techniques to get optimal weights of the attributes to get the aggregated interval-valued intuitionistic fuzzy value of each alternative. Then, it calculates the transformed value of the obtained interval-valued intuitionistic fuzzy value of each alternative. The larger the transformed value, the better the preference order of the alternative. The proposed method can overcome the drawbacks of the existing methods for multiattribute decision making based on interval-valued intuitionistic fuzzy sets. It provides us with a useful way for multiattribute decision making based on interval-valued intuitionistic fuzzy sets, PSO techniques, and the evidential reasoning methodology.

Some aspects of intuitionistic fuzzy sets

Abstract: We first discuss the significant role that duality plays in many aggregation operations involving intuitionistic fuzzy subsets We then consider the extension to intuitionistic fuzzy subsets of a number of ideas from standard fuzzy subsets In particular we look at the measure of specificity We also look at the problem of alternative selection when decision criteria satisfaction is expressed using intuitionistic fuzzy subsets We introduce a decision paradigm called the method of least commitment We briefly look at the problem of defuzzification of intuitionistic fuzzy subsets

An novel approach to supplier selection based on vague sets group decision

Abstract: In practice, in purchasing decision-making, many quantitative and qualitative factors, with vagueness and imprecision, have to be considered. This makes the decision process very complicated and unstructured. Besides the fuzzy sets theory, vague sets theory is one of the methods used to deal with uncertain information. Since vague sets can provide more information than fuzzy sets, it is considered superior in mathematical analysis of uncertain information. In this paper, a new approach based on vague sets group decision is proposed to deal with the supplier selection problem in supply chain systems. The work procedure is shown briefly, as follows: First, linguistic values are used to assess the ratings and weights for quantitative or qualitative factors. Second, degree of similarity and probability of vague sets are used to determine the ranking order of all alternatives. Finally, a numerical example of the selection problem of suppliers is shown, to highlight the procedure of the proposed approach, at the end of this paper.