Multistage decision making based on prioritization of hesitant multiplicative preference relations

Article type: Research Article

Authors: Lin, Yang^{a; b} | Wang, Ying-Ming^{a; *} | Chen, Sheng-Qun^c

Affiliations: [a] Decision Sciences Institute, Fuzhou University, Fuzhou, PR China | [b] School of Economics, Fujian Normal University, Fuzhou, PR China | [c] School of Electronic Information Science, Fujianjiangxia University, Fuzhou, PR China

Correspondence: [*] Corresponding author. Ying-Ming Wang, Decision Sciences Institute, Fuzhou University, Fuzhou 350116, PR China. Tel.: +86 0591 22866677; E-mail: [email protected].

Abstract: Hesitant multiplicative preference relation (HMPR) is a straightforward and efficient tool for representing hesitant fuzzy information in decision making. The aim of this paper is to develop a method to obtain priority vectors from HMPRs in the context of multistage decision-making (MSDM). To start the investigation, a simple linear programming model motivated by the idea of orness is purposed to calculate the relative weights of different stages. Based on these obtained weights, we develop a least square deviation method as well as a convergent iterative algorithm for prioritizing and ranking the MSDM- HMPR problems. The prominent property of this method is then studied. Finally, a practical example concerning the selection of logistics service providers is given to illustrate the feasibility and applicability of the proposed approach.

Keywords: Hesitant fuzzy set, hesitant multiplicative preference relation, multistage decision making, priority ranking, least square deviation method

DOI: 10.3233/JIFS-152630

Journal: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 1, pp. 691-701, 2017