Performance indicators in multiobjective optimization
| Autor: | Dominique Cartier, Sébastien Le Digabel, Jean Bigeon, Charles Audet, Ludovic Salomon |
|---|---|
| Přispěvatelé: | Groupe d’études et de recherche en analyse des décisions (GERAD), École Polytechnique de Montréal (EPM)-McGill University = Université McGill [Montréal, Canada]-HEC Montréal (HEC Montréal)-Université du Québec à Montréal = University of Québec in Montréal (UQAM), Système d’Information, conception RobustE des Produits (G-SCOP_SIREP), Laboratoire des sciences pour la conception, l'optimisation et la production (G-SCOP), Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA) |
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
050210 logistics & transportation
Mathematical optimization Measure (data warehouse) 021103 operations research Information Systems and Management General Computer Science Computer science media_common.quotation_subject 05 social sciences 0211 other engineering and technologies [INFO.INFO-RO]Computer Science [cs]/Operations Research [cs.RO] 02 engineering and technology quality indicators Management Science and Operations Research performance indicators Multi-objective optimization Industrial and Manufacturing Engineering Cardinality Modeling and Simulation 0502 economics and business Quality (business) multiobjective optimization Performance indicator [MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC] media_common |
| Zdroj: | European Journal of Operational Research European Journal of Operational Research, Elsevier, 2020, 292 (2), pp.397-422. ⟨10.1016/j.ejor.2020.11.016⟩ |
| ISSN: | 0377-2217 |
| DOI: | 10.1016/j.ejor.2020.11.016⟩ |
| Popis: | International audience; In recent years, the development of new algorithms for multiobjective optimization has considerably grown. A large number of performance indicators has been introduced to measure the quality of Pareto front approximations produced by these algorithms. In this work, we propose a review of a total of 63 performance indicators partitioned into four groups according to their properties: cardinality, convergence, distribution and spread. Applications of these indicators are presented as well. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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