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A genetic algorithm for berth allocation and quay crane assignment

dc.contributor.authorRodríguez Molins, Mario
dc.contributor.authorBarber, Federico
dc.contributor.authorSierra Sánchez, María Rita 
dc.contributor.authorPuente Peinador, Jorge 
dc.contributor.authorSalido, Miguel A.
dc.date.accessioned2015-11-03T11:12:51Z
dc.date.available2015-11-03T11:12:51Z
dc.date.issued2012
dc.identifier.isbn978-3-642-34653-8
dc.identifier.issn0302-9743
dc.identifier.urihttp://hdl.handle.net/10651/33773
dc.identifier.urihttp://link.springer.com/chapter/10.1007%2F978-3-642-34654-5_61spa
dc.description13th Ibero-American Conference on Artificial Intelligence. IBERAMIA 2012, Cartagena de Indias, Colombia. 13-16 November 2012spa
dc.descriptionThe final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-34654-5_61
dc.description.abstractContainer terminals are facilities where cargo containers are transshipped between different transport vehicles, for onward transportation. They are open systems that carry out a large number of different combinatorial problems that can be solved by means of Artificial Intelligence techniques. In this work, we focus our attention on scheduling a number of incoming vessels by assigning to each a berthing position, a mooring time and a number of Quay Cranes. This problem is known as the Berthing Allocation and Quay Crane Assignment problem. To formulate the problem, we first propose a mixed integer linear programming model to minimize the total weighted service time of the incoming vessels. Then, a meta-heuristic algorithm (Genetic Algorithm (GA)) is presented for solving the proposed problem. Computational experiments are performed to evaluate the effectiveness and efficiency of the proposed methodspa
dc.description.sponsorshipThis research has been supported by the Spanish Government under research project MICINN TIN2010-20976-C02-01 and TIN2010- 20976-C02-02, and the predoctoral FPU fellowship (AP2010-4405)spa
dc.format.extentp. 601-610spa
dc.language.isoengspa
dc.publisherSpringerspa
dc.relation.ispartofAdvances in Artificial Intelligence, IBERAMIA 2012spa
dc.rights© Springer
dc.rightsCC Reconocimiento - No comercial - Sin obras derivadas 4.0 Internacional
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectSchedulingspa
dc.subjectPlanningspa
dc.subjectGenetic algorithmsspa
dc.subjectMetaheuristicsspa
dc.subjectBerthing allocationspa
dc.subjectQuay crane assignmentspa
dc.titleA genetic algorithm for berth allocation and quay crane assignmenteng
dc.typeconference outputspa
dc.identifier.doi10.1007/978-3-642-34654-5_61
dc.relation.projectIDMEC/TIN2010-20976-C02-01
dc.relation.projectIDMEC/TIN2010- 20976-C02-02
dc.rights.accessRightsopen accessspa
dc.type.hasVersionAM


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