TOPSIS-method based on generalized dice similarity measures with hamy mean operators and its application to decision-making process

Abstract

Hamy mean operator is the modified shape of the averaging and geometric aggregation operators, used for evaluation of the collection of finite numbers of attributes into a singleton set. Hamy mean operator is massively valuable and proficient principle to operate awkward and problematic information. In this analysis, we diagnosed the theory of Hamy mean operator based on complex Pythagorean fuzzy (CPF) sets, called CPF Hamy mean (CPFHM), CPF weighted Hamy mean (CPFWHM), CPF dual Hamy mean (CPFDHM), CPF weighted dual Hamy mean (CPFWDHM) operators and evaluate their dominant and valuable results as well as properties. Further, the TOPSIS “Technique for order of preference by similarity to ideal solution” method is also very valuable, computed in this manuscript based on generalized dice similarity measures to improve the worth of the diagnosed theory. Moreover, multi-attribute decision-making (MADM) and the TOPSIS method are two well-known techniques that are used for illustrating the beneficial optimal. Using these two tools, we discovered some numerical examples based on the evaluated operators, measures, and methods to show the feasibility and accuracy of the diagnosed information. Finally, we used some existing information and try to compare it with our evaluated information using our illustrated examples and discussed their geometrical interpretations.