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dc.contributor.authorOliveira, José A.por
dc.contributor.authorFerreira, João Amaro Oliveirapor
dc.contributor.authorFigueiredo, Manuelpor
dc.contributor.authorDias, Luis S.por
dc.contributor.authorPereira, Guilhermepor
dc.descriptionThe authors would like to thank the anonymous reviewers for their valuable comments and suggestions to improve the paper. The authors would like to thank Dr. Elaine DeBock for reviewing the manuscript.por
dc.description.abstractThis study presents three genetic algorithms developed to solve a routing problem related with a transportation service for non- emergency patients in Portugal. A model based on an extension of the Team Orienteering Problem was developed to carry out several legal constraints. The results of computational experiments made to validate the adopted methodology, using both public TOP instances and real data, are presented.por
dc.description.sponsorshipPrograma Operacional Fatores de Competitividade - COMPETE" and by the FCT - Fundação para a Ciência e Tecnologia in the scope of the project: FCOMP-01-0124-FEDER-02267por
dc.publisherSpringer International Publishingpor
dc.subjectGenetic Algorithmpor
dc.subjectJCell frameworkpor
dc.subjectTeam Orienteering Problempor
dc.subjectNon-emergency patients transport servicespor
dc.titleGenetic algorithms for the non emergency patients transport servicepor
sdum.publicationstatusin publicationpor
dc.subject.fosEngenharia e Tecnologia::Outras Engenharias e Tecnologiaspor
sdum.journalAdvances in Intelligent Systems and Computingpor
sdum.conferencePublicationSoft Computing in Industrial Applications: Advances in Intelligent Systems and Computing-
Appears in Collections:CAlg - Artigos em livros de atas/Papers in proceedings

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