EDAS method for multi-attribute decision-making with generalized hesitant fuzzy numbers and its application to energy projects selection

Abstract

Generalized hesitant fuzzy numbers (GHFNs) can reflect the real situation of the event, in which we may encounter limited known values and known values of the set of the degree of doubt, as a quantitative approximation of uncertainty or quantification of linguistic expressions. The score function and weighting method of GHFNs are of great significance in multi-attribute decision-making (MADM) problems. In different ambiguous environments, many scholars have proposed score functions and entropy measures for different fuzzy sets. Firstly, the existed score function of GHFNs was analyzed in detail and a new score function of GHFNs was established by combining previous references. Secondly, a combined weighting method is built based on the minimum identification information principle by fusing GHF entropy and Method based on the Removal Effects of Criteria (MEREC). Thirdly, a novel GHF MADM method (GHF-EDAS) is built by extending evaluation based on distance from average solution (EDAS) method to the GHF environment to solve the issue that the decision attribute information is GHFNs. Finally, the validity and usefulness of the technique are verified by applying the GHF-EDAS technique to energy projects selection and comparing with the existing GHF-MADM method, the practicability and effectiveness of the model are verified, which offer a new way to solve the MADM problem of GHFNs.