CROSS-ENTROPY MEASURES OF MULTIVALUED NEUTROSOPHIC SETS AND ITS APPLICATION IN SELECTING MIDDLE-LEVEL MANAGER

Selecting middle-level managers is a key decision-making issue facing human resource professionals. Multivalued neutrosophic sets (MVNSs), a subset of neutrosophic sets (NSs), is a more flexible and effective method for solving practical middle-level manager selection scenarios than fuzzy sets (FSs). In this paper, in order to address middle-level manager selection decision-making issues, cross-entropy of MVNSs is investigated, and several novel cross-entropy measures between two MVNSs are introduced and their related properties are proven. We then propose two approaches based on the developed cross-entropy measures under the multivalued neutrosophic environment, and within these approaches, an optimal model is devised to determine the weight vector of the criteria with completely unknown information. Finally, the proposed methods are applied to the real selection of middle-level managers, and the ranking results are compared with previously proposed methods to show that the proposed methods are practical and effective.