Applying linguistic information and intersection concept to improve effectiveness of multi-criteria decision analysis technology

Abstract

Multi-criteria decision-making (MCDM) is one of the most widely used decision methodologies. Because every kind of MCDM approach has unique strengths and weaknesses, it is difficult to determine which kind of MCDM approach is best suited to a specific problem. Therefore, a new decision-making method is proposed herein, based on linguistic information and intersection concepts; it is called the linguistic intersection method (LIM). Notably, the linguistic variables are more suited to expressing the opinion of each decision maker. There are four MCDM methods: TOPSIS, ELECTRE, PROMETHEE and VIKOR which are included in the LIM. First, each MCDM approach is used to determine the ranking order of all alternatives in accordance with the linguistic evaluations of decision makers. Then, the intersection set is determined with regard to the better alternatives of all methods. Third, the final ranking order of alternatives in the intersection set can be determined by the proposed method. Lastly, an example is given to describe the procedure of the proposed method. In order to verify the effectiveness of the proposed method, a simulation test is provided to compare the LIM with the linguistic MCDM method. According to the comparison results, the proposed method is more stable in determining the ranking order of all decision alternatives.