Multiple Hierarchically Structured Criteria in ARAS Method Under Fuzzy Environment

Abstract

The aim of multiple criteria decision aiding (MCDA) is to assist decision makers (DMs) to make rational decisions with respect to their preferences. In fact, the ranking approaches are the most used ones nowadays in the MCDA field because they are easy to understand by DMs and they are based on realistic assumptions. The hierarchical additive ratio assessment (ARAS-H) method is a ranking method. It represents an extension of the ARAS method in case of hierarchically structured criteria. However, most often, the DM is unable to provide precise performance values. Henceforth, in order to facilitate the task for him, he is asked to provide linguistic variables. Thus, the authors adopted the fuzzy logic. As a matter of fact, the fuzzy set theory takes into account the subjectivity of experts' ‘judgments.' In the light of the above, the fuzzy ARAS-H (F-ARAS-H) algorithm was developed as an extension of the ARAS-H method in a context of a fuzzy environment. To discuss the feasibility of the proposed algorithm, a case study on the selection of a green supplier was presented.

Identifying Optimal Conceptual Design of a Briquetting Machine

“…Aside from the fuzzy number theory, another mathematical theory that can be applied in the MCDM models is rough number [19]. [20,21,22,23], Weighted Decision Matrix (WDM), Analytic Hierarchy Process (AHP), Analytic Network Process (ANP), Technique for Order Preference by similarity to Ideal Solution (TOPSIS), VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) to mention a few. In some cases, some of these models are hybridized in order to improve the computational process and make the decision process more robust [24,25,26].…”