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dc.date.accessioned 2012-11-02T20:03:52Z
dc.date.available 2012-11-02T20:03:52Z
dc.date.issued 2007
dc.identifier.uri http://sedici.unlp.edu.ar/handle/10915/23576
dc.description.abstract In this paper, the two-dimensional strip packing problem with 3-stage level patterns is tackled using genetic algorithms (GAs). We evaluate the usefulness of a greedy seeding procedure for creating the initial population, incorporating problem knowledge. This is motivated by the expectation that the seeding will speed up the GA by starting the search in promising regions of the search space. An analysis of the impact of the seeded initial population is offered, together with a complete study of the influence of these modifications on the genetic search. The results show that the use of an appropriate seeding of the initial population outperforms existing GA approaches on all the used problem instances, for all the metrics used, and in fact it represents the new state of the art for this problem. es
dc.format.extent 1512-1524 es
dc.language en es
dc.subject Biology and genetics es
dc.subject genetic algorithms en
dc.subject strip packing en
dc.subject Algorithms es
dc.subject seeding en
dc.title Greedy seeding procedure for GAs solving a strip packing problem en
dc.type Objeto de conferencia es
sedici.creator.person Salto, Carolina es
sedici.creator.person Alba Torres, Enrique es
sedici.creator.person Molina, J.M. es
sedici.creator.person Leguizamón, Guillermo es
sedici.subject.materias Ciencias Informáticas es
sedici.subject.materias Informática es
sedici.description.fulltext true es
mods.originInfo.place Red de Universidades con Carreras en Informática (RedUNCI) es
sedici.subtype Objeto de conferencia es
sedici.rights.license Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
sedici.rights.uri http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
sedici.date.exposure 2007-10
sedici.relation.event XIII Congreso Argentino de Ciencias de la Computación es
sedici.description.peerReview peer-review es


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Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5) Except where otherwise noted, this item's license is described as Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)