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dc.contributor.authorElliott, Gregory
dc.contributor.authorJiang, Fuming
dc.contributor.authorRedding, Gordon
dc.contributor.authorStening, Bruce
dc.date.accessioned2017-12-02T14:41:30Z
dc.date.available2017-12-02T14:41:30Z
dc.date.issued2010
dc.identifier.urihttp://hdl.handle.net/20.500.12127/3737
dc.description.abstractIn this paper we present a genetic algorithm for the multi-mode resource-constrained project scheduling problem (MRCPSP), in which multiple execution modes are available for each of the activities of the project. We also introduce the preemptive extension of the problem which allows activity splitting (P-MRCPSP). To solve the problem, we apply a bi-population genetic algorithm, which makes use of two separate populations and extend the serial schedule generation scheme by introducing a mode improvement procedure. We evaluate the impact of preemption on the quality of the schedule and present detailed comparative computational results for the MRCPSP, which reveal that our procedure is amongst the most competitive algorithms.
dc.language.isoen
dc.subjectStrategic Context & International Business
dc.titleThe Chinese business environment in the next decade: Report from a Delphi study
dc.identifier.journalAsian Business & Management
dc.source.volume9
dc.source.issue4
dc.source.beginpage459
dc.source.endpage480
vlerick.knowledgedomainStrategy
vlerick.typearticleJournal article with impact factor
vlerick.vlerickdepartmentP&O
dc.identifier.vperid140609
dc.identifier.vperid140789
dc.identifier.vperid141042
dc.identifier.vperid116623
dc.identifier.vpubid4262


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