Belief interval interpretation of probabilistic linguistic term sets and a visual method for solving the preference problem in multicriteria group decision making. Issue 8 (25th May 2021)

• Record Type: Journal Article
• Authors: Dong, Yuanxiang; Cheng, Xiaoting; Xu, Zeshui; Chen, Weijie; Shi, Hongbo; Gong, Ke
• Is Part Of: International journal of intelligent systems. Volume 36:Issue 8(2021)
• Page Start: 4364
• Page End: 4391
• Publication Date: 2021-05-25
• Subjects: belief interval -- multicriteria group decision making -- preference problem -- probabilistic linguistic term sets -- visual algorithm; Artificial intelligence -- Periodicals; Expert systems (Computer science) -- Periodicals; Intelligence artificielle -- Périodiques; Systèmes experts (Informatique) -- Périodiques; 006.3
• DOI: 10.1002/int.22463
• Languages: English
• ISSNs: 0884-8173

Abstract

Abstract: For the application of probabilistic linguistic term sets (PLTSs) in multicriteria group decision making (MCGDM), this paper aims to develop an approach to solve the preference problem. First, a belief interval interpretation of PLTSs is presented, which makes it possible to represent the mathematical operations on PLTSs as the operations on belief intervals. This can reduce the uncertainty degree of information caused by the differentiated knowledge and cognitions of decision makers. Then, two methods of belief interval measure are proposed. One is the distance measure, which is utilized to obtain the criteria weights of each decision maker, so as to recognize the preferences for criteria. The other is the probability degree, which is used to get the partial order relation for alternatives of each decision maker, and to recognize the preferences for alternatives. Next, employing Dempster's rule of combination and graph theory, a visual algorithm is constructed to solve the MCGDM preference problem in the application of PLTSs. Finally, an illustrative example for the selection of emergency materials deployment scheme and the comparative analyses are shown to demonstrate the effectiveness of the proposed method.