CRM-based dynamic decision-making with hesitant fuzzy information for the evaluation of rangelands

Abstract

As one of the important components of global land ecosystem, rangeland ecosystem has important value of ecosystem services. With the degeneration of rangeland in recent years, sustainability within rangeland ecosystem has become an increasingly important issue. The aim of this paper is to develop a novel dynamic decision-making approach based on hesitant fuzzy information to evaluate rangeland sustainability that considers ecological, social and economic aspects. Firstly, a modified satisfaction degree of alternative is presented, based on which a mathematical model for determining the stage weights is constructed. Secondly, the compromise ratio method (CRM), whose basic principle is that the optimal alternative should have the nearest distance from positive ideal solution and the longest distance from negative ideal solution simultaneously, is extended to accommodate hesitant fuzzy environment, and then adopted to tackle the dynamic decision-making with hesitant fuzzy information. Compared with the existing methods, the proposed method can eliminate the impact of attribute magnitude and dimension. Lastly, a numerical example on the evaluation of rangelands is provided to illustrate the practicality and superiority of the proposed method.

Keywords

• hesitant fuzzy set
• dynamic decision-making
• compromise ratio method
• satisfaction degree
• rangeland sustainability evaluation