A New Similarity Measure for Rankings Obtained in MCDM Problems Using Different Normalization Techniques
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...
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| Main Author: | |
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| Format: | Article |
| Language: | English |
| Published: |
Wrocław University of Science and Technology
2024-01-01
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| Series: | Operations Research and Decisions |
| Online Access: | https://ord.pwr.edu.pl/assets/papers_archive/ord2024vol34no2_4.pdf |
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| Summary: | 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. (original abstract) |
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| ISSN: | 2081-8858 2391-6060 |