Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/35282

TitleSolving the RCPSP with an evolutionary algorithm based on instance information
Author(s)Oliveira, José A.
Dias, Luís M. S.
Pereira, Guilherme
KeywordsGenetic algorithm
Metaheuristics
Optimization
Project management
Random keys
RCPSP
Scheduling
Issue date2012
PublisherSCITEPRESS – Science and Technology Publications
CitationOliveira, 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
Abstract(s)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.
TypeConference paper
URIhttp://hdl.handle.net/1822/35282
ISBN978-989-8425-97-3
DOI10.5220/0003759401570164
Publisher versionhttp://www.scitepress.org/DigitalLibrary/Link.aspx?doi=10.5220/0003759401570164
Peer-Reviewedyes
AccessRestricted access (UMinho)
Appears in Collections:CAlg - Artigos em livros de atas/Papers in proceedings

Files in This Item:
File Description SizeFormat 
art2012_ICORES.pdf
  Restricted access
Artigo completo392,76 kBAdobe PDFView/Open    Request a copy!

Partilhe no FacebookPartilhe no TwitterPartilhe no DeliciousPartilhe no LinkedInPartilhe no DiggAdicionar ao Google BookmarksPartilhe no MySpacePartilhe no Orkut
Exporte no formato BibTex mendeley Exporte no formato Endnote Adicione ao seu ORCID