Generalized orthopair fuzzy weighted distance‐based approximation (WDBA) algorithm in emergency decision‐making. Issue 10 (12th August 2019)

• Record Type: Journal Article
• Authors: Peng, Xindong; Krishankumar, Raghunathan; Ravichandran, Kattur Soundarapandian
• Is Part Of: International journal of intelligent systems. Volume 34:Issue 10(2019)
• Page Start: 2364
• Page End: 2402
• Publication Date: 2019-08-12
• Subjects: deviation‐based method -- q‐rung orthopair fuzzy set -- score function -- weighted distance‐based approximation; Artificial intelligence -- Periodicals; Expert systems (Computer science) -- Periodicals; Intelligence artificielle -- Périodiques; Systèmes experts (Informatique) -- Périodiques; 006.3
• DOI: 10.1002/int.22140
• Languages: English
• ISSNs: 0884-8173

Abstract

Abstract: With the intensification of global warming trends, the frequent occurrence of natural disasters has brought severe challenges to the sustainable development of society. Emergency decision‐making (EDM) in natural disasters is playing an increasingly important role in improving disaster response capacity. In the case of EDM evaluation, the essential problem arises serious incompleteness, impreciseness, subjectivity, and incertitude. The q‐ rung orthopair fuzzy set ( q‐ ROFS), disposing the indeterminacy portrayed by membership and nonmembership with the sum of q th power of them, is a more viable and effective means to seize indeterminacy. The aim of paper is to present a new score function of q‐ rung orthopair fuzzy number ( q‐ ROFN) for solving the failure problems when comparing two q‐ ROFNs. Firstly, we introduce some basic set operations for q‐ ROFS. The properties of these operations are also discussed in detail. Later, we propose a q‐ rung orthopair fuzzy decision‐making method based on weighted distance‐based approximation (WDBA), in which the weights of decision‐makers are obtained from a nonliner optimization model according to the deviation‐based method. Finally, some examples are investigated to illustrate the feasibility and validity of the proposed approach. The salient features of the proposed method, compared to the existing q‐ rung orthopair fuzzy decision‐making methods, are as follows: (a) it can obtain the optimal alternative without counterintuitive phenomena and (b) it has a great power in distinguishing the optimal alternative.