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https://hdl.handle.net/1822/35282
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Campo DC | Valor | Idioma |
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dc.contributor.author | Oliveira, José A. | por |
dc.contributor.author | Dias, Luís M. S. | por |
dc.contributor.author | Pereira, Guilherme | por |
dc.date.accessioned | 2015-05-26T14:51:35Z | - |
dc.date.available | 2015-05-26T14:51:35Z | - |
dc.date.issued | 2012 | - |
dc.identifier.citation | Oliveira, J.A.; Dias, L.; Pereira, G.; ,Solving the RCPSP with an evolutionary algorithm based on instance information,"1st International Conference on Operations Research and Enterprise Systems, ICORES 2012, Vilamoura, Portugal, February 4-6, ISBN 978-989-8425-97-3. pp. 157-164 | por |
dc.identifier.isbn | 978-989-8425-97-3 | - |
dc.identifier.uri | https://hdl.handle.net/1822/35282 | - |
dc.description.abstract | The Resource Constrained Project Scheduling Problem (RCPSP) is NP-hard thus justifying the use meta-heuristics for its solution. This paper presents an evolutionary algorithm developed for the RCPSP problem. This evolutionary algorithm uses an alphabet based on random keys that makes easier its implementation while solving combinatorial optimization problems. Random keys allow the use of conventional genetic operators, what makes easier the adaptation of the evolutionary algorithm to new problems. To improve the method's performance, this evolutionary algorithm uses an initial population that is generated considering the information available for the instance. This paper studies the impact of using that information in the initial population. The computational experiments presented compare two types of initial population - the conventional one (generated randomly) and this new approach that considers the information of the instance. | por |
dc.description.sponsorship | Fundação para a Ciência e a Tecnologia (FCT) | por |
dc.language.iso | eng | por |
dc.publisher | SCITEPRESS – Science and Technology Publications | por |
dc.relation | Projeto Estratégico do Centro Algoritmi | por |
dc.rights | restrictedAccess | por |
dc.subject | Genetic algorithm | por |
dc.subject | Metaheuristics | por |
dc.subject | Optimization | por |
dc.subject | Project management | por |
dc.subject | Random keys | por |
dc.subject | RCPSP | por |
dc.subject | Scheduling | por |
dc.title | Solving the RCPSP with an evolutionary algorithm based on instance information | por |
dc.type | conferencePaper | por |
dc.peerreviewed | yes | por |
dc.relation.publisherversion | http://www.scitepress.org/DigitalLibrary/Link.aspx?doi=10.5220/0003759401570164 | por |
sdum.publicationstatus | published | por |
oaire.citationStartPage | 157 | por |
oaire.citationEndPage | 164 | por |
oaire.citationConferencePlace | Vilamoura, Portugal | por |
oaire.citationTitle | Proceedings of the 1st International Conference on Operations Research and Enterprise Systems (ICORES 2012) | por |
dc.identifier.doi | 10.5220/0003759401570164 | por |
dc.subject.fos | Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática | por |
dc.subject.fos | Engenharia e Tecnologia::Outras Engenharias e Tecnologias | por |
sdum.conferencePublication | Proceedings of the 1st International Conference on Operations Research and Enterprise Systems (ICORES 2012) | por |
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art2012_ICORES.pdf Acesso restrito! | Artigo completo | 392,76 kB | Adobe PDF | Ver/Abrir |