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A genetic algorithm for berth allocation and quay crane assignment
dc.contributor.author | Rodríguez Molins, Mario | |
dc.contributor.author | Barber, Federico | |
dc.contributor.author | Sierra Sánchez, María Rita | |
dc.contributor.author | Puente Peinador, Jorge | |
dc.contributor.author | Salido, Miguel A. | |
dc.date.accessioned | 2015-11-03T11:12:51Z | |
dc.date.available | 2015-11-03T11:12:51Z | |
dc.date.issued | 2012 | |
dc.identifier.isbn | 978-3-642-34653-8 | |
dc.identifier.issn | 0302-9743 | |
dc.identifier.uri | http://hdl.handle.net/10651/33773 | |
dc.identifier.uri | http://link.springer.com/chapter/10.1007%2F978-3-642-34654-5_61 | spa |
dc.description | 13th Ibero-American Conference on Artificial Intelligence. IBERAMIA 2012, Cartagena de Indias, Colombia. 13-16 November 2012 | spa |
dc.description | The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-34654-5_61 | |
dc.description.abstract | Container 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 method | spa |
dc.description.sponsorship | This 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.extent | p. 601-610 | spa |
dc.language.iso | eng | spa |
dc.publisher | Springer | spa |
dc.relation.ispartof | Advances in Artificial Intelligence, IBERAMIA 2012 | spa |
dc.rights | © Springer | |
dc.rights | CC Reconocimiento - No comercial - Sin obras derivadas 4.0 Internacional | |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | |
dc.subject | Scheduling | spa |
dc.subject | Planning | spa |
dc.subject | Genetic algorithms | spa |
dc.subject | Metaheuristics | spa |
dc.subject | Berthing allocation | spa |
dc.subject | Quay crane assignment | spa |
dc.title | A genetic algorithm for berth allocation and quay crane assignment | eng |
dc.type | conference output | spa |
dc.identifier.doi | 10.1007/978-3-642-34654-5_61 | |
dc.relation.projectID | MEC/TIN2010-20976-C02-01 | |
dc.relation.projectID | MEC/TIN2010- 20976-C02-02 | |
dc.rights.accessRights | open access | spa |
dc.type.hasVersion | AM |
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