Industrial Engineering, University of Tehran
Department of Energy Economics, Economics Faculty, University of Tehran
In recent two decades, countries focused on minimum extraction of fossil fuels and utilized the renewable energies based on countries' policies and the environmental considerations. Thus, choosing the best renewable energy alternative is a significant role to investment on them. Among the classical decision approaches that have used in the literature, the hesitant fuzzy sets (HFSs) theory is appropriate tool to deal with uncertain and imprecise condition. The HFSs could help experts or decision makers in energy sector to consider some membership degrees for a renewable energy alternative regarding to conflicted criteria under a set. The aim of this paper is to propose a hierarchical complex proportional assessment (COPRAS) method to consider subjective judgments and objective opinions based on HFS theory for multi-criteria group decision making (MCGDM) problems. In addition, the hesitant fuzzy decision matrix as well as sub-criteria and main criteria are defined based on linguistic variables and then converted to hesitant fuzzy elements. In the proposed approach, weights of experts are different and computed by proposed hesitant fuzzy entropy method. Also, weights of main criteria are determined by a new relation in n level of hierarchy structure with experts' risk preferences. Finally, a real case study in Iran about the renewable energy selection in hierarchy structure is presented and hesitant fuzzy hierarchical complex proportional assessment (HF-HCOPRAS) method is applied to show the efficiency and practically of the proposed approach.