Abstract
As a result of the heterogeneity of decision-makers, it is more suitable to use multi-granular linguistic information to express assessing information over alternatives for decision-makers. Decision-makers may only provide partial preference information as the limitation of knowledge over the alternatives. Thus, the incomplete multi-granular 2-tuple fuzzy linguistic preference relations (IMGFLPRs) can be applied to manage the GDM problems in complex environments. In this paper, we propose a novel group decision-making (GDM) model based on mathematical programming with IMGFLPRs. It is more important that the proposed mathematical programming can directly deal with IMGFLPRs and does not need to be converted into a uniform form. By this means, we construct a consensus reaching process based on IMGFLPRs, considering simultaneously dynamic adjustment of experts’ weight. Finally, an emergency plan selection problem is solved by the proposed model, which shows the result of GDM is effectiveness.
Highlights
With the development of society, decision-making environments are more and more complex and uncertain
We propose a novel group decision-making (GDM) model based on mathematical programming with IMGFLPRs
For linguistic information-based GDM problems, multiple DMs with different level of cognitive competence and knowledge may engage in the decisionmaking process, which usually implies the necessity of multiple linguistic scales to express properly different knowledge for different DMs [2]
Summary
With the development of society, decision-making environments are more and more complex and uncertain. Preference relation is a useful tool for DMs to provide their preferences information on alternatives, for example multiplicative preference relation [10], fuzzy preference relation (FPR) [11] and linguistic preference relation (LPR) [12], etc It is well understood in the field of decisionmaking that an expert might not possess adequate levels of knowledge or information to address a given decisionmaking problem [13], incomplete evaluations can occur in the complex environment. A large number of models have already been proposed to manage GDM problems based on incomplete multi-granular 2-tuple fuzzy linguistic preference relations (IMGFLPRs) [4, 8], there are some drawbacks to the existing research.
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