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dc.date.accessioned 2012-10-17T13:55:54Z
dc.date.available 2012-10-17T13:55:54Z
dc.date.issued 2004
dc.identifier.uri http://sedici.unlp.edu.ar/handle/10915/22554
dc.description.abstract Parallel machine scheduling, involves the allocation of jobs to the system resources (a bank of machines in parallel). A basic model consisting of m machines and n jobs is the foundation of more complex models. Here, jobs are allocated according to resource availability following some allocation rule. In the specialised literature, minimisation of the makespan has been extensively approached and benchmarks can be easily found. This is not the case for other important objectives such as the maximum tardiness and the number of tardy jobs. These problems are NP-hard for 2 ≤ m ≤ n, and conventional heuristics and evolutionary algorithms (EAs) have been developed to provide acceptable schedules as solutions. To solve the unrestricted identical parallel machine scheduling problems, this paper proposes MCMP-SRI and MCMP-SRSI, which are two multirecombination schemes that combine studs, random and seed immigrants. Evidence of the improved behaviour of the EAs when inserting problem-specific knowledge is provided. Experiments and results are discussed. en
dc.language en es
dc.subject Parallel es
dc.subject Parallel machine scheduling en
dc.subject Scheduling es
dc.subject evolutionary algorithms en
dc.subject multirecombination en
dc.subject Algorithms es
dc.subject maximum tardiness en
dc.subject ARTIFICIAL INTELLIGENCE es
dc.subject number of tardy jobs en
dc.subject Intelligent agents es
dc.title Evolutionary optimization of due date based objectives in unrestricted identical parallel machine scheduling problems en
dc.type Objeto de conferencia es
sedici.creator.person Ferretti, Edgardo es
sedici.creator.person Esquivel, Susana Cecilia es
sedici.creator.person Gallard, Raúl Hector es
sedici.description.note Eje: V - Workshop de agentes y sistemas inteligentes 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 2004-10
sedici.relation.event X 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)