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A genetic algorithm for robust berth allocation and quay crane assignment

dc.contributor.authorRodríguez Molins, Mario
dc.contributor.authorIngolotti, Laura
dc.contributor.authorBarber, Federico
dc.contributor.authorSalido, Miguel A.
dc.contributor.authorSierra Sánchez, María Rita 
dc.contributor.authorPuente Peinador, Jorge 
dc.date.accessioned2016-04-15T11:09:05Z
dc.date.available2016-04-15T11:09:05Z
dc.date.issued2014-07
dc.identifier.citationProgress in Artificial Intelligence, 2(4), p. 177-192 (2014); doi:10.1007/s13748-014-0056-3
dc.identifier.issn2192-6352
dc.identifier.issn2192-6360
dc.identifier.urihttp://hdl.handle.net/10651/36673
dc.description.abstractScheduling problems usually obtain the optimal solutions assuming that the environment is deterministic. However, actually the environment is dynamic and uncertain. Thus, the initial data could change and the initial schedule obtained might be unfeasible. To overcome this issue, a proactive approach is presented for scheduling problems without any previous knowledge about the incidences that can occur. In this paper, we consider the berth allocation problem and the quay crane assignment problem as a representative example of scheduling problems where a typical objective is to minimize the service time. The robustness is introduced within this problem by means of buffer times that should be maximized to absorb possible incidences or breakdowns. Therefore, this problem becomes a multi-objective optimization problem with two opposite objectives: minimizing the total service time and maximizing the robustness or buffer times
dc.description.sponsorshipThis research was supported by the Spanish Government under research projects TIN2010-20976-C02-01 and TIN2010-20976-C02-02 (Min. de Ciencia e Innovación, Spain), the project PIRSES-GA-2011-294931 (FP7-PEOPLE-2011-IRSES) and the predoctoral FPU fellowship (AP2010-4405)spa
dc.format.extentp. 177-192spa
dc.language.isoengspa
dc.publisherSpringerspa
dc.relation.ispartofProgress in Artificial Intelligence, 2(4)spa
dc.rights© 2014 Springer
dc.rightsCC Reconocimiento - No comercial - Sin obras derivadas 4.0 Internacional
dc.rightshttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectScheduling
dc.subjectPlanning
dc.subjectRobustness
dc.subjectGenetic algorithms
dc.titleA genetic algorithm for robust berth allocation and quay crane assignmenteng
dc.typejournal articlespa
dc.identifier.doi10.1007/s13748-014-0056-3
dc.relation.projectIDMEC/TIN2010-20976-C02
dc.relation.projectIDMEC/TIN2010-20976-C02-02
dc.relation.projectIDPIRSES-GA-2011-294931 (FP7-PEOPLE-2011-IRSES)
dc.relation.publisherversionhttp://dx.doi.org/10.1007/s13748-014-0056-3spa
dc.rights.accessRightsopen access
dc.type.hasVersionAM


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