Distance measures of hesitant complex neutrosophic sets and their applications in decision-making

The fuzzy set (FS) and its generalizations are important tools in modelling decision-making problems. Although the FS is a successful tool in modeling one-dimensional information, it is insufficient in modeling two-dimensional information. This weakness is corrected with complex fuzzy set (CFS), which is a successful structure in representing two-dimensional information. In addition, the hesitant fuzzy set (HFS) is a very useful argument in group decision-making problems. The complex neutrosophic set (CNS) is an extension of the FS that was recently identified and attracted the attention of researchers. In this study, the concept of hesitant complex neutrosophic set (HCNS) is defined by combining the concepts of CNS and HFS. Also, distance measures between two HCNSs based on Euclidean, Hamming and Hausdorff distance measures are introduced and some relationships between them are examined. Moreover, a decision-making method using the proposed distance measures has been developed and an example including the computer purchasing problem is given to show the application process of the developed method.