D-WASPAS: Addressing Social Cognition in Uncertain Decision-Making with an Application to a Sustainable Project Portfolio Problem

• Published in: Cognitive computation 2020-05, Vol.12 (3), p.619-641
• Main Authors: Mohagheghi, Vahid, Mousavi, S. Meysam
• Format: Article
• Language: English
• Subjects: Alternatives; Artificial Intelligence; Biomedical and Life Sciences; Biomedicine; Cognition; Cognition & reasoning; Computation by Abstract Devices; Computational Biology/Bioinformatics; Critical path; Decision analysis; Decision making; Fuzzy sets; Judgments; Methods; Multiple criterion; Neurosciences; Ranking; Similarity measures; Uncertainty
• ISSN: 1866-9956; 1866-9964
• DOI: 10.1007/s12559-019-09679-3

Decision-making is an interdisciplinary area that has roots in mathematics, economics, and social science. Multiple-criteria group decision-making (MCGDM) is one of the most applicable areas of decision-making. Social cognition is involved in group decision-making. Therefore, it is necessary to address how decision makers (DMs) process and apply judgments and information during the process. In recent years, many approaches have been applied to MCGDM. As an important aspect of this process, uncertainty has led to the application of fuzzy sets. However, utilizing various decision-making approaches can result in different results and confusion among DMs. Moreover, using classic fuzzy sets and expressing degrees of belonging by crisp values has proven to be inadequate for uncertain decision-making environments. This paper presents a novel MCGDM approach, double-weighted aggregated sum product assessment (D-WASPAS), under interval-valued Pythagorean fuzzy (IVPF) uncertainty. The proposed approach applies knowledge measures to address the objective weights of criteria. Then, subjective and objective weights of criteria are aggregated to create a more appropriate weight. This approach considers three decision-making methods. In the first, an IVPF-ARAS (additive ratio assessment) method is extended to rank the alternatives. In the second, an IVPF-EDAS (evaluation based on distance from average solution) method is developed to rank the alternatives. In the third, a novel IVPF-COADAP (complex adequate appraisal) method is utilized for a third ranking. To aggregate the results, two steps are carried out using the WASPAS method. First, the results of the ranking approaches are aggregated. This process starts with computing the objective weights of the ranking approaches and aggregating the outcome with the subjective weights of the approaches. Then, the WASPAS method is applied to aggregate the obtained rankings and obtain a set of rankings for each DM. The second aggregation is utilized to aggregate the results for the DMs and reach a final set of rankings. Similarly, the subjective and objective weights of the DMs are applied in the WASPAS to aggregate the results. It should be noted that since the WASPAS method is utilized twice to aggregate the results, this approach is called D-WASPAS. A case study of the application of the proposed method shows that it is applicable to many multiple-criteria analysis and decision-making processes. Moreover, the results are more