A Hybrid Fuzzy MCDM Approach To Thesis Subject Selection

Abstract

One of the most significant decisions that a doctoral student may make in the beginning of his/her research career is the selection of a thesis subject. There are also a number of conflicting criteria, including supervisor reputation, convergence of interest, student's interest and motivation, etc, which should be considered as a part of the appropriate thesis subject selection process. For this purpose, multiple criteria decision making (MCDM) methods have been found to be useful approaches to solve this kind of problem. This paper devises a fuzzy hybrid analytical hierarchy process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS) approach to the problem of thesis subject selection. Fuzzy AHP is used to calculate the weight of each criterion, and fuzzy TOPSIS is proposed to prioritize thesis subjects from the best to the worst ones. The application of fuzzy set theory allows incorporating the vague and imprecise linguistic terms into the decision process.