Evolving Parameterised Policies for Stochastic Constraint Programming
| dc.contributor.author | Prestwich S. | |
| dc.contributor.author | Tarim S.A. | |
| dc.contributor.author | Rossi R. | |
| dc.contributor.author | Hnich B. | |
| dc.date.accessioned | 2023-06-16T14:58:01Z | |
| dc.date.available | 2023-06-16T14:58:01Z | |
| dc.date.issued | 2009 | |
| dc.description | Association for Constraint Programming (ACP);Natl. Inf. Commun. Technol. Australia NICTA;Foundation for Science and Technology (FCT);Centre for Artificial Intelligence (CENTRIA);Portuguese Association for Artificial Intelligence (APPIA) | en_US |
| dc.description | 15th International Conference on Principles and Practice of Constraint Programming, CP 2009 -- 20 September 2009 through 24 September 2009 -- Lisbon -- 77835 | en_US |
| dc.description.abstract | Stochastic Constraint Programming is an extension of Constraint Programming for modelling and solving combinatorial problems involving uncertainty. A solution to such a problem is a policy tree that specifies decision variable assignments in each scenario. Several solution methods have been proposed but none seems practical for large multi-stage problems. We propose an incomplete approach: specifying a policy tree indirectly by a parameterised function, whose parameter values are found by evolutionary search. On some problems this method is orders of magnitude faster than a state-of-the-art scenario-based approach, and it also provides a very compact representation of policy trees. © 2009 Springer Berlin Heidelberg. | en_US |
| dc.description.sponsorship | SOBAG-108K027; Science Foundation Ireland, SFI: 05/IN/I886; Türkiye Bilimsel ve Teknolojik Araştirma Kurumu, TÜBITAK | en_US |
| dc.description.sponsorship | B. Hnich is supported by the Scientific and Technological Research Council of Turkey (TUBITAK) under Grant No. SOBAG-108K027. This material is based in part upon works supported by the Science Foundation Ireland under Grant No. 05/IN/I886. | en_US |
| dc.identifier.doi | 10.1007/978-3-642-04244-7_53 | |
| dc.identifier.isbn | 3642042430 | |
| dc.identifier.isbn | 9783642042430 | |
| dc.identifier.issn | 0302-9743 | |
| dc.identifier.scopus | 2-s2.0-70350423545 | |
| dc.identifier.uri | https://doi.org/10.1007/978-3-642-04244-7_53 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.14365/3400 | |
| dc.language.iso | en | en_US |
| dc.relation.ispartof | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | en_US |
| dc.rights | info:eu-repo/semantics/closedAccess | en_US |
| dc.subject | Combinatorial problem | en_US |
| dc.subject | Compact representation | en_US |
| dc.subject | Constraint programming | en_US |
| dc.subject | Decision variables | en_US |
| dc.subject | Evolutionary search | en_US |
| dc.subject | Multi-stage problem | en_US |
| dc.subject | Orders of magnitude | en_US |
| dc.subject | Parameter values | en_US |
| dc.subject | Solution methods | en_US |
| dc.subject | Stochastic constraints | en_US |
| dc.subject | Computer programming | en_US |
| dc.subject | Constraint theory | en_US |
| dc.subject | Evolutionary algorithms | en_US |
| dc.subject | Unmanned aerial vehicles (UAV) | en_US |
| dc.subject | Problem solving | en_US |
| dc.title | Evolving Parameterised Policies for Stochastic Constraint Programming | en_US |
| dc.type | Conference Object | en_US |
| dspace.entity.type | Publication | |
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| gdc.description.departmenttemp | Prestwich, S., Cork Constraint Computation Centre, University College Cork, Ireland; Tarim, S.A., Operations Management Division, Nottingham University Business School, Nottingham, United Kingdom; Rossi, R., Logistics, Decision and Information Sciences Group, Wageningen UR, Netherlands; Hnich, B., Faculty of Computer Science, Izmir University of Economics, Turkey | en_US |
| gdc.description.endpage | 691 | en_US |
| gdc.description.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | en_US |
| gdc.description.scopusquality | Q3 | |
| gdc.description.startpage | 684 | en_US |
| gdc.description.volume | 5732 LNCS | en_US |
| gdc.description.wosquality | N/A | |
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