MEPSI (Mutriss Enhanced Preference Selection Index): a novel method for ranking alternatives

This paper introduces a novel method named Mutriss Enhanced Preference Selection Index (MEPSI) for ranking alternatives. MEPSI is a hybrid of MUTRISS (Multiple-Triangles Scenarios) and PSI (Preference Selection Index). In this study, PSI is utilized with two distinct functions: one as a ranking function for alternatives, also known as Multi-Criteria Decision Making (MCDM), and the other as a weighting function for criteria. The criteria weights calculated by the PSI method are used to rank the alternatives using the MUTRISS method. Thus, for each specific problem, the combination of MUTRISS and PSI provides two sets of ranking data for the alternatives: one from using PSI and the other from the hybrid MUTRISS-PSI method. This hybrid forms a new method called MEPSI. Accuracy tests for MEPSI were conducted on various problems. The tests conducted are all related to the ranking of different types of materials in various applications. Case 1 is to rank five types of materials used for manufacturing car shock absorbers, each specified by six criteria. Case 2 is to rank nine types of materials used for manufacturing gears, each with five criteria. And Case 3 is to rank four types of materials used for manufacturing connecting rods, each specified by 15 criteria. In these tests, the accuracy of MEPSI was evaluated using Spearman's rank correlation coefficient by comparing the ranking results of alternatives using MEPSI against other methods. The results indicated no significant differences in the rankings of alternatives when ranked by MEPSI compared to other methods. Most importantly, the top-ranked alternative found by MEPSI consistently matched the top rank identified by other MCDM methods. This study proposes MEPSI as a highly accurate method to the repository of MCDM methods