4.7 Article

A decision support model for group decision making with hesitant multiplicative preference relations

期刊

INFORMATION SCIENCES
卷 282, 期 -, 页码 136-166

出版社

ELSEVIER SCIENCE INC
DOI: 10.1016/j.ins.2014.05.057

关键词

Hesitant fuzzy set (HFS); Hesitant multiplicative set (HMS); Hesitant multiplicative preference relation (HMPR); Consistency; Consensus

资金

  1. National Natural Science Foundation of China [61073121, 71271070, 61375075]
  2. Natural Science Foundation of the Hebei Province of China [F2012201020, A2012201033]

向作者/读者索取更多资源

The hesitant fuzzy preference relation (HFPR) was recently introduced by Zhu and Xu to allow the decision makers (DMs) to offer several possible preference values over two alternatives. In this paper, we use an asymmetrical scale (Saaty's 1-9 scale) to express the decision makers' preference information instead of the symmetrical scale that is found in a HFPR, and we introduce a new preference structure that is known as the hesitant multiplicative preference relation (HMPR). Each element of the HMPR is characterized by several possible preference values from the closed interval [1/9, 91; thus, it can model decision makers' hesitation more accurately and reflect people's intuitions more objectively. Furthermore, we develop a consistency- and consensus-based decision support model for group decision making (GDM) with hesitant multiplicative preference relations (HMPRs). In this model, an individual consistency index is defined to measure the degree of deviation between an HMPR and its consistent HMPR, and a consistency improving process is designed to convert an unacceptably consistent HMPR to an acceptably consistent HMPR. Additionally, a group consensus index is introduced to measure the degree of deviation between the individual HMPRs and the group HMPR, and a consensus-reaching process is provided to help the individual HMPRs achieve a predefined consensus level. Finally, a numerical example is provided to demonstrate the practicality and effectiveness of the developed model. (C) 2014 Elsevier Inc. All rights reserved.

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