Dynamic Emergency Decision-Making Method With Probabilistic Hesitant Fuzzy Information Based on GM(1,1) and TOPSIS

Abstract

Decision-makers (DMs) will face severe challenges when selecting an optimal alternative for an emergency response over multiple time periods. The aim of this paper is to develop a novel dynamic emergency decision-making method with probabilistic hesitant fuzzy information for handling emergencies. First, an approach based on the GM(1,1) model for predicting the decision-making information at the next stage is proposed. Second, a new probabilistic hesitant fuzzy distance measure based on the hesitant degree of the probabilistic hesitant fuzzy element is put forward, and a mathematical programming model to determine the stage weights is established. What is more, the closeness degree between each alternative and the ideal alternative is calculated, and the emergency alternatives are ranked on the strength of the technique for order preference by similarity to an ideal solution method. Moreover, a practical example is used to verify the feasibility and rationality of the proposed method. INDEX TERMSDynamic emergency decision-making, probabilistic hesitant fuzzy set (PHFS), GM(1,1) model, TOPSIS method. degree in pure mathematics from Wuhan University, and management science from College of Economics and Management at Nanjing University of Aeronautics and Astronautics, China, respectively. He is an Associate Professor in the school of mathematics and Physics at Anhui University of Technology. His research areas are multiple attribute decision making, clustering analysis, and aggregation operators. His articles are published in the Technological and Economic

INVESTMENT DECISION MAKING ALONG THE B&R USING CRITIC APPROACH IN PROBABILISTIC HESITANT FUZZY ENVIRONMENT

“…Besides, they offered an entropybased approach for investment decision making. With the aid of hesitant degree of PHFE, Wu et al (2019) presented a new distance for PHFSs. Obviously, distance measures have been proven to be useful in MADM (Liu et al, 2018).…”

“…membership degree values and their corresponding probabilities, and thus can reserve much more information in MADM (Zhang et al, 2017). Up to now, PHFSs have been used in emergency response (Gao et al, 2017;Wu et al, 2019), cluster analysis (Song et al, 2019) and consensus-based decision making (Li & Wang, 2018;Wu et al, 2018;Xu & Zhou, 2017). Li and Wang (2017) adopted the QUALIFLEX approach based on PHFSs to evaluate the green suppliers.…”

Probabilistic hesitant fuzzy multiple attribute decision-making based on regret theory for the evaluation of venture capital projects

“…As pointed by Dadras, Momeni, and Majd (2008), uncertainty is widely found in the complex realities (Wang, Gao, Wei, & Wei, 2019;Wu, Liu, Wang, & Zhang, 2019;Wu, Wang & Gao, 2019). To model the uncertainty, Torra (2010) proposed the concept of hesitant fuzzy set (H.F.S.…”

“…P.H.F.S. depicts not only the hesitancy of decision-makers when they are irresolute for one thing or another, but also the hesitant distribution information (Li & Wang, 2018;Wu, Liu, et al, 2019). Afterwards, Zhang, Xu, and He (2017) defined the operations over P.H.F.S.s and presented an improved P.H.F.S.…”

Recommendation decision-making algorithm for sharing accommodation using probabilistic hesitant fuzzy sets and bipartite network projection

“…Furthermore, the operation rules and aggregation operators of PHFSs are defined by Zhang et al [49]. Subsequently, it was applied to various fields such as decision-making [50,51], supply chain management [52], project investment [53], and so on. Due to the uncertainty of users' recommendation content, PHFS which can be thought as an effective tool for modeling the uncertainty is utilized to present the evaluation information in this paper.…”