Spherical Cubic Fuzzy Extended TOPSIS Method and Its Application in Multicriteria Decision-Making

Abstract

This paper aims to propose a new methodology for spherical cubic fuzzy (SCF) multicriteria decision-making (MCDM) utilizing the TOPSIS method that uses incomplete weight information. At first, the maximum deviation model is suggested to determine the criteria of weight values. An MCDM methodology is introduced using SCF information, based on the proposed method. Also, to validate the effectiveness of the proposed information, a numerical example is given. Finally, a comprehensive and structured analysis of existing work in comparison with previous work is given.

An Integrated Spherical Cubic Fuzzy ELECTRE-I Decision-Making Algorithm for Enhancing Online Banking Security

“…The superiority and effectiveness of our proposed SCF-ELECTRE I method is verified by implementing the SCF-TOPSIS method [28] on the given case study.The results obtained from the comparative analysis can be summarized and compiled in the following manner.…”

“…• By using SCF-TOPSIS method [28], the SCF P IS and SCF N IS are determined in Table 5.1. 5.2 shows the distances between each option and the ideal solution, as well as the ranks of alternatives based on the relative proximity index ρ.…”

“…5.2 shows the distances between each option and the ideal solution, as well as the ranks of alternatives based on the relative proximity index ρ. [28])…”

“…After that, Tehreem et al [27] introduced dombi aggregation operators dealing with SCFSs and explored their application in MCDM. In addition, Tehreem et al [28] proposed extended version of TOPSIS method under SCF environment with unknown criteria weights assessment through maximum deviation methodology. Jagtap and Karanda [17] calculated the effect of normalization methods on rank performance in singlevalued m-polar fuzzy ELECTRE-I method.…”

Extended ELECTRE Method for Multi-Criteria Group Decision-Making with Spherical Cubic Fuzzy Sets

“…After that, Tehreem et al [35] introduced dombi aggregation operators dealing with SCFSs and explored their application in MCDM. In addition, Tehreem et al [36] proposed extended version of TOPSIS method under SCF environment with unknown criteria weights assessment through maximum deviation methodology. Jagtap and Karanda [20] calculated the effect of normalization methods on rank performance in singlevalued m-polar fuzzy ELECTRE-I method.…”