Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/26213

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dc.contributor.authorFerreira, João Amaro Oliveira-
dc.contributor.authorOliveira, José A.-
dc.contributor.authorPereira, Guilherme-
dc.contributor.authorDias, Luís M. S.-
dc.contributor.authorVieira, Fernando-
dc.contributor.authorMacedo, João-
dc.contributor.authorCarção, Tiago-
dc.contributor.authorLeite, Tiago-
dc.contributor.authorMurta, Daniel R.-
dc.date.accessioned2013-11-21T11:02:09Z-
dc.date.available2013-11-21T11:02:09Z-
dc.date.issued2013-02-16-
dc.identifier.isbn978-989-8565-40-2-
dc.identifier.urihttp://hdl.handle.net/1822/26213-
dc.description.abstractPresently, the large-scale collection process of selective waste is typically expensive, with low efficiency and moderate effectiveness. Despite the abundance of commercially available software for fleet management, real life managers are only minimally helped by it when dealing with resource and budgetary requirements, scheduling activities, and acquiring resources for their accomplishment within the constraints imposed on them. To overcome these issues, we intend to develop a solution that optimizes the waste collection process by modelling this problem as a vehicle routing problem, in particular as a Team Orienteering Problem (TOP). In the TOP, a vehicle fleet is assigned to visit a set customers, while executing optimized routes that maximize total profit and minimize resources needed. In this work, we propose to solve the TOP using a genetic algorithm, in order to achieve challenging results in comparison to previous work around this subject of study. Our objective is to develop and evaluate a software application that implements a genetic algorithm to solve the TOP. We were able to accomplish the proposed task and achieved interesting results with the computational tests by attaining the best known results in half of the tested instances.por
dc.description.sponsorshipThis study is partially supported by FEDER Funds through the COMPETE - Programa Operacional Fatores de Competitividade and by national funds by FCT – Fundação para a Ciência e Tecnologiain the scope of the Project: FCOMP-01-0124-FEDER-022674, and GATOP - Genetic Algorithms for Team Orienteering Problem (Ref PTDC/EME-GIN/120761/2010), financed by national funds by FCT / MCTES, and co-funded by the European Social Development Fund (FEDER) through the COMPETE - Programa Operacional Fatores de Competitividade (POFC) Ref FCOMP-01-0124-FEDER-020609.por
dc.language.isoengpor
dc.publisherSCITEPRESS – Science and Technology Publicationspor
dc.relationinfo:eu-repo/grantAgreement/FCT/5876-PPCDTI/120761/PT-
dc.relationinfo:eu-repo/grantAgreement/FCT/COMPETE/120761/PT-
dc.rightsrestrictedAccesspor
dc.subjectRouting problemspor
dc.subjectTeam Orienteering Problempor
dc.subjectOptimizationpor
dc.subjectMetaheuristicspor
dc.subjectGenetic algorithmpor
dc.titleDeveloping tools for the team orienteering problem: a simple genetic algorithmpor
dc.typeconferencePaperpor
dc.peerreviewedyespor
sdum.publicationstatuspublishedpor
oaire.citationStartPage134por
oaire.citationEndPage140por
oaire.citationConferencePlaceBarcelona, Espanhapor
oaire.citationTitle2nd International Conference on Operations Research and Enterprise Systems (ICORES 2013)por
sdum.conferencePublication2nd International Conference on Operations Research and Enterprise Systems (ICORES 2013)por
Appears in Collections:CAlg - Artigos em revistas internacionais/Papers in international journals

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