A novel cubical fuzzy score function for the location selection of wind farm using linear assignment method

Abstract

In an uncertain context, extensions of the fuzzy set have a substantial impact in multiple criteria decision making (MCDM) situations. Cubical fuzzy set (CFS), is one such extension that is more advantageous for handling impreciseness in MCDM problems. The comparison of cubical fuzzy numbers (CFNs) is a signicant stage in the cubical fuzzy decision making process. In literature, it is found that the existing ranking functions fails to compare CFNs in certain situations. In order to address this issue, the current paper focuses on dening a new score function that compares CFNs in all circumstances. A comparison study is made with the literature to show the potency of the proposed score function. In multiple criteria problems, nding criteria weights plays a vital phase during the decision making process. Taking into account, this paper adopted the subjective method of pairwise comparison for determining the criteria objective weights. Further, a cubical fuzzy linear assignment method (CF-LAM) based on the proposed score function for solving a cubical fuzzy multiple criteria group decision making (CF-MCGDM) problem has been developed. The practical applicability and feasibility of the proposed score function using the developed LAM are illustrated by solving a real life MCGDM problem of nding the best location for the construction of a wind power farm under a CF environment.