Towards Faster Performance of PROMETHEE II in a Lower Class of Complexity

PROMETHEE II is one of the most popular members of the well-known family of multi-criteria decision making methods. One of the main concerns in developing PROMETHEE-based systems is the rapid growth of the response time as the number of alternatives (n) and criteria (k) grow. PROMETHEE II belongs to the computational complexity class of O(n توان ۲). In this paper, a simplified version of PROMETHEE II is proposed and a novel estimation of the simplified PROMETHEE II is introduced. This simplified version reproduces the results of the original method and requires fewer operations. The estimation belongs to the complexity class of O(n log n) and consequently has a shorter response time than that of the simplified version. The proposed simplification and estimation are tested and evaluated with real-world data. When compared to the original PROMETHEE II and even other similar MCDM methods, such as AHP, ELECTRA, and TOPSIS, the experiments reveal the satisfactory results with a considerably reduced computational complexity and response time.

Keywords:

multi criteria decision making , PROMETHEE II , decision support systems , recommender systems