Multiple Criteria Decision-Making (MCDM) is one of the most reliable and applicable decision-making tools to address real-life complex and multi-dimensional problems in accordance with the concepts of sustainable development and circular economy. Although there have been several literature reviews on several MCDM methods, there is a research gap in conducting a literature review on the Multi-Attributive Border Approximation area Comparison (MABAC) as a useful technique to deal with intelligent decision-making systems. This study attempts to present a comprehensive literature review of 117 articles on recent developments and applications of MABAC. Future outlook is provided considering challenges and current trends.
Pub. online:15 Oct 2020Type:Research ArticleOpen Access
Journal:Informatica
Volume 32, Issue 1 (2021), pp. 119–143
Abstract
The objective of the paper is to introduce a novel approach using the multi-attribute border approximation area comparison (MABAC) approach under intuitionistic fuzzy sets (IFSs) to solve the smartphone selection problem with incomplete weights or completely unknown weights. A novel discrimination measure of IFSs is proposed to calculate criteria weights. In view of the fact that the ambiguity is an unavoidable feature of multiple-criteria decision-making (MCDM) problems, the proposed approach is an innovative process in the decision-making under uncertain settings. To express the utility and strength of the developed approach for solving problems in the area of MCDM, a smartphone selection problem is demonstrated. To validate the IF-MABAC approach, a comparative discussion is made between the outcomes of the developed and those of the existing methods. The outcomes of analysis demonstrate that the introduced method is well-ordered and effective with the existing ones.