Linguistic hesitant fuzzy multi-criterion decision-making for renewable energy: A case study in Jilin

Renewable energy is the inevitable choice for the sustainable development of society and economy. How to select the most appropriate renewable energy for a region is a complex multi-criterion decision making (MCDM) problem. Taking Jilin Province as an example, this paper proposes a new MCDM method. In order to better express the hesitancy, inconsistency and uncertainty of decision makers' preferences, linguistic hesitant fuzzy set (LHFS) is proposed. On the basis of cloud model, the rule of transforming LHFS to quantitative values is defined. Subsequently, the distance measure and support measure are established. In consideration of the interdependency of criteria, an LHFS aggregation operator based on improved Choquet integral is proposed. Finally, the ranking result of the aggregated LHFS corresponding to each renewable energy alternative is obtained according to the expectation values. The result shows that the preferred renewable energy for Jilin is biomass energy, followed by wind energy, hydro energy and solar energy. The validation analysis and comparison analysis are given to demonstrate the effectiveness of the proposed method. (C) 2017 Elsevier Ltd. All rights reserved.