Fifty years of multiple criteria decision analysis: From classical methods to robust ordinal regression
Multiple Criteria Decision Analysis (MCDA) is a subfield of Operational Research that aims to support Decision-Makers (DMs) in the decision-making process through mathematical models and computational procedures. In this perspective, MCDA employs structured and traceable protocols to identify potent...
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| Vydané v: | European journal of operational research Ročník 323; číslo 2; s. 351 - 377 |
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| Hlavní autori: | , , |
| Médium: | Journal Article |
| Jazyk: | English |
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Elsevier B.V
01.06.2025
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| ISSN: | 0377-2217 |
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| Abstract | Multiple Criteria Decision Analysis (MCDA) is a subfield of Operational Research that aims to support Decision-Makers (DMs) in the decision-making process through mathematical models and computational procedures. In this perspective, MCDA employs structured and traceable protocols to identify potential actions and the criteria for evaluating them. MCDA procedures aim to define recommendations consistent with the preferences of DMs for the specific decision problem at hand. These problems are generally formulated in terms of either choosing the best action, classifying actions into pre-defined and ordered decision classes, or ranking actions from best to worst. As the evaluation criteria are generally conflicting, the main challenge is to aggregate them into a mathematical preference model representing the DM value system. We review the development of MCDA over the past fifty years and describe its evolution with examples of distinctive methods. They are distinguished by the type of preference information elicited by DMs, the type of the preference model (criteria aggregation), and the way of converting the preference relation induced by the preference model in the set of potential actions into a decision recommendation. We focus on MCDA methods with a finite set of actions. References to specific application areas will be given. In the conclusion section, some prospective avenues of research will be outlined.
•We review the evolution of Multiple Criteria Decision Analysis over the past 50 years.•Distinct methods from various Multiple Criteria Decision Analysis schools are presented.•Focus is on preference elicitation, criteria aggregation, and recommendation development.•A general overview is followed by perspectives and a future research agenda. |
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| AbstractList | Multiple Criteria Decision Analysis (MCDA) is a subfield of Operational Research that aims to support Decision-Makers (DMs) in the decision-making process through mathematical models and computational procedures. In this perspective, MCDA employs structured and traceable protocols to identify potential actions and the criteria for evaluating them. MCDA procedures aim to define recommendations consistent with the preferences of DMs for the specific decision problem at hand. These problems are generally formulated in terms of either choosing the best action, classifying actions into pre-defined and ordered decision classes, or ranking actions from best to worst. As the evaluation criteria are generally conflicting, the main challenge is to aggregate them into a mathematical preference model representing the DM value system. We review the development of MCDA over the past fifty years and describe its evolution with examples of distinctive methods. They are distinguished by the type of preference information elicited by DMs, the type of the preference model (criteria aggregation), and the way of converting the preference relation induced by the preference model in the set of potential actions into a decision recommendation. We focus on MCDA methods with a finite set of actions. References to specific application areas will be given. In the conclusion section, some prospective avenues of research will be outlined.
•We review the evolution of Multiple Criteria Decision Analysis over the past 50 years.•Distinct methods from various Multiple Criteria Decision Analysis schools are presented.•Focus is on preference elicitation, criteria aggregation, and recommendation development.•A general overview is followed by perspectives and a future research agenda. |
| Author | Greco, Salvatore Słowiński, Roman Wallenius, Jyrki |
| Author_xml | – sequence: 1 givenname: Salvatore orcidid: 0000-0001-8293-8227 surname: Greco fullname: Greco, Salvatore organization: Department of Economics and Business, University of Catania, 95129 Catania, Italy – sequence: 2 givenname: Roman orcidid: 0000-0002-5200-7795 surname: Słowiński fullname: Słowiński, Roman email: roman.slowinski@cs.put.poznan.pl organization: Institute of Computing Science, Poznań University of Technology, 60-965 Poznań, Poland – sequence: 3 givenname: Jyrki surname: Wallenius fullname: Wallenius, Jyrki organization: School of Business, Aalto University, P.O. Box 11000, 00076 Aalto, Finland |
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| Keywords | Preference modeling Ranking Ordinal classification Multiple criteria decision analysis Best choice |
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| Title | Fifty years of multiple criteria decision analysis: From classical methods to robust ordinal regression |
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