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Multi-objective evolutionary search strategies in constraint programming
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| Veröffentlicht in: | Operations research perspectives 8(2021), Artikel-ID 100177, Seite 1-15 |
|---|---|
| Personen und Körperschaften: | , |
| Titel: | Multi-objective evolutionary search strategies in constraint programming/ Robert Bennetto, Jan H van Vuuren |
| Format: | E-Book-Kapitel |
| Sprache: | Englisch |
| veröffentlicht: |
2021
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| Gesamtaufnahme: |
: Operations research perspectives, 8(2021), Artikel-ID 100177, Seite 1-15
, volume:8 |
| Schlagwörter: | |
| Quelle: | Verbunddaten SWB Lizenzfreie Online-Ressourcen |
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| contents | It has been shown that evolutionary algorithms are able to construct suitable search strategies for classes of Constraint Satisfaction Problems (CSPs) in Constraint Programming. This paper is an explanation of the use of multi-objective optimisation in contrast to simple additive weighting techniques with a view to develop search strategies to classes of CSPs. A hierarchical scheme is employed to select a candidate strategy from the Pareto frontier for final evaluation. The results demonstrate that multi-objective optimisation significantly outperforms the single objective scheme in the same number of objective evaluations. In situations where strategies developed for a class of problems fail to extend to unseen problem instances of the same class, it is found that the structure of the underlying CSPs do not resemble those employed in the training process. |
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| spelling | Bennetto, Robert VerfasserIn aut, Multi-objective evolutionary search strategies in constraint programming Robert Bennetto, Jan H van Vuuren, 2021, Text txt rdacontent, Computermedien c rdamedia, Online-Ressource cr rdacarrier, DE-206 Open Access Controlled Vocabulary for Access Rights http://purl.org/coar/access_right/c_abf2, It has been shown that evolutionary algorithms are able to construct suitable search strategies for classes of Constraint Satisfaction Problems (CSPs) in Constraint Programming. This paper is an explanation of the use of multi-objective optimisation in contrast to simple additive weighting techniques with a view to develop search strategies to classes of CSPs. A hierarchical scheme is employed to select a candidate strategy from the Pareto frontier for final evaluation. The results demonstrate that multi-objective optimisation significantly outperforms the single objective scheme in the same number of objective evaluations. In situations where strategies developed for a class of problems fail to extend to unseen problem instances of the same class, it is found that the structure of the underlying CSPs do not resemble those employed in the training process., DE-206 Namensnennung 4.0 International CC BY 4.0 cc https://creativecommons.org/licenses/by/4.0/, 1.1\x Constraint-Programmierung (DE-627)769491618 (DE-2867)29775-3 stw, 1.2\x Multikriterielle Entscheidungsanalyse (DE-627)091378885 (DE-2867)15476-4 stw, 1.3\x Evolutionärer Algorithmus (DE-627)091407842 (DE-2867)29402-0 stw, 1.4\x Metaheuristik (DE-627)799281832 (DE-2867)29923-0 stw, 1.5\x Kombinatorische Optimierung (DE-627)769533329 (DE-2867)29777-6 stw, Combinatorial optimization, Constraint programming, Genetic algorithms, Multi-objective optimization, Aufsatz in Zeitschrift DE-206, Vuuren, Jan van VerfasserIn (DE-588)139434143 (DE-627)610394118 (DE-576)311744303 aut, Enthalten in Operations research perspectives Amsterdam [u.a.] : Elsevier, 2014 8(2021), Artikel-ID 100177, Seite 1-15 Online-Ressource (DE-627)826105165 (DE-600)2821932-6 (DE-576)433076496 2214-7160 nnns, volume:8 year:2021 elocationid:100177 pages:1-15, https://www.sciencedirect.com/science/article/pii/S2214716020300671/pdfft?md5=d6d8c42610cfced210f222af7508b7fa&pid=1-s2.0-S2214716020300671-main.pdf Verlag kostenfrei, https://doi.org/10.1016/j.orp.2020.100177 Resolving-System kostenfrei, http://hdl.handle.net/10419/246437 Resolving-System kostenfrei, https://doi.org/10.1016/j.orp.2020.100177 LFER, https://www.sciencedirect.com/science/article/pii/S2214716020300671/pdfft?md5=d6d8c42610cfced210f222af7508b7fa&pid=1-s2.0-S2214716020300671-main.pdf LFER, LFER 2021-03-10T04:53:30Z |
| spellingShingle | Bennetto, Robert, Vuuren, Jan van, Multi-objective evolutionary search strategies in constraint programming, It has been shown that evolutionary algorithms are able to construct suitable search strategies for classes of Constraint Satisfaction Problems (CSPs) in Constraint Programming. This paper is an explanation of the use of multi-objective optimisation in contrast to simple additive weighting techniques with a view to develop search strategies to classes of CSPs. A hierarchical scheme is employed to select a candidate strategy from the Pareto frontier for final evaluation. The results demonstrate that multi-objective optimisation significantly outperforms the single objective scheme in the same number of objective evaluations. In situations where strategies developed for a class of problems fail to extend to unseen problem instances of the same class, it is found that the structure of the underlying CSPs do not resemble those employed in the training process., Constraint-Programmierung, Multikriterielle Entscheidungsanalyse, Evolutionärer Algorithmus, Metaheuristik, Kombinatorische Optimierung, Combinatorial optimization, Constraint programming, Genetic algorithms, Multi-objective optimization, Aufsatz in Zeitschrift |
| title | Multi-objective evolutionary search strategies in constraint programming |
| title_auth | Multi-objective evolutionary search strategies in constraint programming |
| title_full | Multi-objective evolutionary search strategies in constraint programming Robert Bennetto, Jan H van Vuuren |
| title_fullStr | Multi-objective evolutionary search strategies in constraint programming Robert Bennetto, Jan H van Vuuren |
| title_full_unstemmed | Multi-objective evolutionary search strategies in constraint programming Robert Bennetto, Jan H van Vuuren |
| title_in_hierarchy | Multi-objective evolutionary search strategies in constraint programming / Robert Bennetto, Jan H van Vuuren, |
| title_short | Multi-objective evolutionary search strategies in constraint programming |
| title_sort | multi objective evolutionary search strategies in constraint programming |
| topic | Constraint-Programmierung, Multikriterielle Entscheidungsanalyse, Evolutionärer Algorithmus, Metaheuristik, Kombinatorische Optimierung, Combinatorial optimization, Constraint programming, Genetic algorithms, Multi-objective optimization, Aufsatz in Zeitschrift |
| topic_facet | Constraint-Programmierung, Multikriterielle Entscheidungsanalyse, Evolutionärer Algorithmus, Metaheuristik, Kombinatorische Optimierung, Combinatorial optimization, Constraint programming, Genetic algorithms, Multi-objective optimization, Aufsatz in Zeitschrift |
| url | https://www.sciencedirect.com/science/article/pii/S2214716020300671/pdfft?md5=d6d8c42610cfced210f222af7508b7fa&pid=1-s2.0-S2214716020300671-main.pdf, https://doi.org/10.1016/j.orp.2020.100177, http://hdl.handle.net/10419/246437 |