Strategies on admissible total orders over typical hesitant fuzzy implications applied to decision making problems. Issue 5 (23rd February 2021)

• Record Type: Journal Article
• Authors: Matzenauer, Mônica; Reiser, Renata; Santos, Hélida; Bedregal, Benjamín; Bustince, Humberto
• Is Part Of: International journal of intelligent systems. Volume 36:Issue 5(2021)
• Page Start: 2144
• Page End: 2182
• Publication Date: 2021-02-23
• Subjects: admissible orders -- aggregation functions -- decision‐making problem -- fuzzy implication functions -- typical hesitant fuzzy sets; Artificial intelligence -- Periodicals; Expert systems (Computer science) -- Periodicals; Intelligence artificielle -- Périodiques; Systèmes experts (Informatique) -- Périodiques; 006.3
• DOI: 10.1002/int.22374
• Languages: English
• ISSNs: 0884-8173

Abstract

Abstract: Multi Expert‐Multi Criteria Decision Making (ME‐MCDM) problems have been well explored on hesitant fuzzy environments dealing with membership degrees as subsets which do not necessarily have the same cardinality. Admissible (total) orders collaborate by reducing the collapse in the ranking of alternatives related to preference relations. In such context, three classes of admissible orders are presented in a non‐restrictive way, integrating the concepts of linearity and cardinality and providing support to the comparison between two typical hesitant fuzzy elements. In the sense of hesitant fuzzy logic, the study of fuzzy operators and their main properties is extended considering the admissible linear orders. Namely, the typical hesitant fuzzy aggregation functions, negations and implication functions are discussed mainly related to their (iso/anti)tonicity properties w.r.t. these admissible orders. An algorithmic procedure is introduced illustrating our strategy to solve an ME‐MCDM problem, by selecting a Computer Integrating Manufacturing software and making use of the achieved theoretical results.