Priority Degrees and Distance Measures of Complex Hesitant Fuzzy Sets With Application to Multi-Criteria Decision Making

The notion of a complex hesitant fuzzy set (CHFS) is one the better tools in order to deal with information. Since distance plays crucial role differentiate between two things or sets, this paper, we first develop priority degree for comparison elements (HFEs). Then variety measures are developed, namely, Complex normalized Hamming-Hausdorff (CHNHHD), Euclidean-Hausdorff (CHNEHD), Generalized Hausdorff (GCHNHD), hybrid Hamming (CHHNHD), Euclidean (CHHNED), (GCHHND) and their weighted forms. Moreover, continuous form proposed distances also developed. Further, applied medical diagnosis problems effectiveness application. Furthermore, multi-criteria decision making (MCDM) approach developed based on TOPSIS method distances. Finally, practical example related COVID-19 tests presented application validity method. A study was done that already place see how well new worked.