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| Format: | Preprint |
| Veröffentlicht: |
2025
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| Online-Zugang: | https://arxiv.org/abs/2508.16087 |
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| _version_ | 1866914006732636160 |
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| author | Wang, Zhiyuan Rangaiah, Gade Pandu |
| author_facet | Wang, Zhiyuan Rangaiah, Gade Pandu |
| contents | This chapter describes selected reference-type multi-criteria decision-making (MCDM) methods that rank alternatives by comparing them with one or more reference solutions derived from an alternatives-criteria matrix (ACM). After explaining the idea of constructing positive ideal, negative ideal and/or average reference solutions, the chapter details the algorithmic steps of each method, illustrating them with a common ACM example. The 9 methods covered are: Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), Gray/Grey Relational Analysis (GRA), VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR), Evaluation Based on Distance from Average Solution (EDAS), Multi-attributive Border Approximation Area Comparison (MABAC), Combinative Distance-based Assessment (CODAS), Proximity Indexed Value (PIV), Measurement of Alternatives and Ranking According to Compromise Solution (MARCOS) and Preference Ranking on the Basis of Ideal-average Distance (PROBID). The advantages (e.g., computational simplicity) and limitations (e.g., susceptibility to rank reversal) of each method are discussed. A consolidated summary highlights how the different treatments of reference solutions can ultimately drive variations in the ranking of alternatives, underscoring the value of applying several methods in practice. By studying this chapter, readers can (1) describe the principles and steps of each reference-type method, (2) implement them on an ACM, and (3) choose an appropriate reference-type method for their decision-making problems. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2508_16087 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Chapter 7 Multi-Criteria Decision-Making: Reference-Type Methods Wang, Zhiyuan Rangaiah, Gade Pandu Optimization and Control This chapter describes selected reference-type multi-criteria decision-making (MCDM) methods that rank alternatives by comparing them with one or more reference solutions derived from an alternatives-criteria matrix (ACM). After explaining the idea of constructing positive ideal, negative ideal and/or average reference solutions, the chapter details the algorithmic steps of each method, illustrating them with a common ACM example. The 9 methods covered are: Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), Gray/Grey Relational Analysis (GRA), VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR), Evaluation Based on Distance from Average Solution (EDAS), Multi-attributive Border Approximation Area Comparison (MABAC), Combinative Distance-based Assessment (CODAS), Proximity Indexed Value (PIV), Measurement of Alternatives and Ranking According to Compromise Solution (MARCOS) and Preference Ranking on the Basis of Ideal-average Distance (PROBID). The advantages (e.g., computational simplicity) and limitations (e.g., susceptibility to rank reversal) of each method are discussed. A consolidated summary highlights how the different treatments of reference solutions can ultimately drive variations in the ranking of alternatives, underscoring the value of applying several methods in practice. By studying this chapter, readers can (1) describe the principles and steps of each reference-type method, (2) implement them on an ACM, and (3) choose an appropriate reference-type method for their decision-making problems. |
| title | Chapter 7 Multi-Criteria Decision-Making: Reference-Type Methods |
| topic | Optimization and Control |
| url | https://arxiv.org/abs/2508.16087 |