Intuitionistic Multi-Criteria Decision Analysis Models and Methods and Applications on Consumer Decision Problems

Multiple Criteria Decision Analysis (MCDA) problems are an important research field in decision science, management science, systems engineering, and operations research. Since classical MCDA methods cannot effectively handle problems with imprecise information, the theory of fuzzy sets, first introduced by Zadeh in 1965, is used to resolve this difficulty. But in reality, it may not always be certain that the evaluation of membership values. There may be some hesitation degree between membership and nonmembership. In view that there are many real life situations where due to insufficiency in information availability, intuitionistic fuzzy sets are appropriate to deal with such problems. Intuitionistic fuzzy set (IFS), introduced by Atanassov in 1986, is characterized by three functions expressing the degree of belongingness, the degree of nonbelongingness, and the degree of hesitation. The concept of IFSs is a generalization of fuzzy sets. IFSs have been found to be particularly useful to deal with vagueness. In this research project, the vagueness and incomplete preference information problems in MCDA will be dealt with IFS theory. We intend to extend compensatory models in MCDA, including compromising models, outranking models, and scoring models, for the sake of appropriate for the intuitionistic fuzzy environment. The detailed models and methods for multiattribute decision making using intuitionistic fuzzy values will be propounded correspondingly. The research period of this project is three years, and the topic for each year is as follow: (i) Intuitionistic Fuzzy Compromising Model in MCDA; (ii) Intuitionistic Fuzzy Outranking Model in MCDA; and (iii) Intuitionistic Fuzzy Scoring Model in MCDA. In this three-years research project, we will develop different decision models and methods for multiple criteria decision making problems in an intuitionistic fuzzy environment. The proposed new models consist of intuitionistic fuzzy compromising, outranking, and scoring methods. Furthermore, computational experiments will be implemented on a large scale in order to draw extensive numerical comparisons. Real-word applications on consumer decision problems will be conducted to examine the feasibility and validity of the proposed intuitionistic fuzzy decision methods as well. We apply the proposed methods on limited and extensive decision making problems in a hedonic or utilitarian manner. These new methods not only improve the existing methods of MCDA but also explore new directions for the permeation of the IFS theory to application areas in practice.

Project ID:PF9709-0824
External Project ID:NSC97-2410-H182-007-MY2