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dc.date.accessioned | 2012-11-01T14:01:03Z | |
dc.date.available | 2012-11-01T14:01:03Z | |
dc.date.issued | 2000-10 | |
dc.identifier.uri | http://sedici.unlp.edu.ar/handle/10915/23428 | |
dc.description.abstract | Over the past few years, a continually increasing number of research efforts have investigated the application of evolutionary computation techniques for the solution of scheduling problems. Scheduling problems can pose extremely complex combinatorial optimization problems, which belong to the NP-hard family. This work shows how an evolutionary approach using different chromosome representations with multiplicity feature MCMP can efficiently solve the JSSP. | en |
dc.language | en | es |
dc.subject | evolutionary algorithms | en |
dc.subject | Scheduling | es |
dc.subject | multiplicity | en |
dc.subject | Optimization | es |
dc.title | A comparison of two multirecombinated evolutionary algorithms for the job shop scheduling problem | en |
dc.type | Objeto de conferencia | es |
sedici.creator.person | Minetti, Gabriela F. | es |
sedici.creator.person | Salto, Carolina | es |
sedici.creator.person | Alfonso, Hugo | es |
sedici.creator.person | Gallard, Raúl Hector | es |
sedici.description.note | I Workshop de Agentes y Sistemas Inteligentes (WASI) | es |
sedici.subject.materias | Ciencias Informáticas | 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 | 2000-10 | |
sedici.relation.event | VI Congreso Argentino de Ciencias de la Computación | es |
sedici.description.peerReview | peer-review | es |