An Improved ELECTRE II-Based Outranking Method for MADM with Double Hierarchy Hesitant Fuzzy Linguistic Sets and Its Application to Emergency Logistics Provider Selection

The emergency logistics provider selection (ELPS) is an important part of emergency logistics management. In an increasingly complex and highly uncertain evaluation environment, how to effectively select emergency logistics providers has become a hot topic in the field of emergency logistics management. In this paper, by integrating the double hierarchy hesitant fuzzy linguistic term set (DHHFLTS), the normalized projection measure and the improved ELECTRE II method, a practical integrated decision support model is proposed to handle the ELPS problem. First, DHHFLTSs are utilized to represent the complex and uncertain linguistic evaluation information provided by decision makers (DMs) to provide subjective judgments. Meanwhile, a distance measure for DHHFLTSs based on the proposed normalized projection is proposed to reflect both the included angle and the distance between evaluation objects, and a weight-determining method based on the proposed distance measure and the maximizing deviation method is constructed. Then a new decision support framework of double hierarchy hesitant fuzzy linguistic ELECTRE II based on positive and negative ideal solutions is put forward, in which three kinds of preference relations of the concordance and discordance sets are set up to rank the alternatives more reasonably. Finally, a practical example of ELPS is presented to illustrate the effectiveness of the proposed method, and detailed comparative analysis with other representative methods is also conducted to demonstrate the advantages of the proposed method.