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dc.date.accessioned 2012-11-01T14:05:24Z
dc.date.available 2012-11-01T14:05:24Z
dc.date.issued 2000-10
dc.identifier.uri http://sedici.unlp.edu.ar/handle/10915/23430
dc.description.abstract A variety of optimization problems in fields such as production operations in manufacturing industry, parallel and distributed systems, logistics and traffic can be summarized within the general class of scheduling problems. A common feature of this problems is that they belong to the class of NP-complete problems, which means that no deterministic algorithm is known yet for solving them in polynomial time. The major advantage of evolutionary techniques resides in their ability of providing good solutions to extremely complex problems in reasonable time. This work introduces MCMP-PRB to face the Job Shop Scheduling Problem (JSSP). Enhancements include a multiplicity feature (MCMP) and a further hybridization with a conventional heuristic know as the priority dispatching rule. en
dc.language en es
dc.subject evolutionary algorithms en
dc.subject Scheduling es
dc.subject chromosome representation en
dc.subject Optimization es
dc.subject multiplicity en
dc.title A hybrid evolutionary algorithm: multirecombination with priority rule base representation abstract for the job shop scheduling problem en
dc.type Objeto de conferencia es
sedici.creator.person Salto, Carolina es
sedici.creator.person Minetti, Gabriela F. 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


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Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5) Excepto donde se diga explícitamente, este item se publica bajo la siguiente licencia Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)