Issue: 2024/Vol.34/No.2, Pages 47-64
A NEW SIMILARITY MEASURE FOR RANKINGS OBTAINED IN MCDM PROBLEMS USING DIFFERENT NORMALIZATION TECHNIQUES
Dariusz Kacprzak
Cite as: D. Kacprzak. A new similarity measure for rankings obtained in MCDM problems using different normalization techniques. Operations Research and Decisions 2024: 34(2), 47-64. DOI 10.37190/ord240204
Abstract
The paper presents an analysis of the impact of normalization techniques on the ranking of alternatives obtained using the combined compromise solution (CoCoSo) method. Similarity measures known from the literature and a new measure called the TOPSIS similarity measure (TOPSIS-SM) are used to assess the resulting rankings. This new measure is based on the TOPSIS algorithm, where the arithmetic mean of the considered rankings is taken as the ideal solution. In contrast, the antiideal solution is divided into a minimum and a maximum solution, which exhibit maximum separation from the ideal solution. The results obtained by this new method are different from those obtained using other similarity measures known from the literature.
Keywords: CoCoSo method, normalization techniques, similarity measures, a new TOPSIS similarity measure
Received: 27 April 2023 Accepted: 4 April 2024
Published online: 8 July 2024