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dc.contributor.authorAlba-Torres, Enrique 
dc.contributor.authorChicano, Francisco 
dc.date.accessioned2014-10-01T08:05:49Z
dc.date.available2014-10-01T08:05:49Z
dc.date.issued2014-10-01
dc.identifier.otherdoi: 10.1016/j.ins.2006.12.020
dc.identifier.urihttp://hdl.handle.net/10630/8145
dc.descriptionInformation Sciences, 177 (11), 2007, pp.2380-2401.es_ES
dc.description.abstractA Project Scheduling Problem consists in deciding who does what during the software project lifetime. This is a capital issue in the practice of software engineering, since the total budget and human resources involved must be managed optimally in order to end in a successful project. In short, companies are principally concerned with reducing the duration and cost of projects, and these two goals are in conflict with each other. In this work we tackle the problem by using genetic algorithms (GAs) to solve many different software project scenarios. Thanks to our newly developed instance generator we can perform structured studies on the influence the most important problem attributes have on the solutions. Our conclusions show that GAs are quite flexible and accurate for this application, and an important tool for automatic project management.es_ES
dc.description.sponsorshipMinistry of Science and Technology (MCYT) and Regional Development European Found (FEDER) under contract TIN2005-08818-C04-01 (the OPLINK project). Francisco Chicano was supported by a Grant (BOJA 68/2003) from the Junta de Andalucía (Spain).es_ES
dc.language.isoenges_ES
dc.rightsinfo:eu-repo/semantics/openAccesses_ES
dc.subjectAlgoritmos genéticoses_ES
dc.subject.otherAutomatic software managementes_ES
dc.subject.otherGenetic algorithmes_ES
dc.subject.otherProject schedulinges_ES
dc.titleSoftware project management with GAses_ES
dc.typeinfo:eu-repo/semantics/preprintes_ES
dc.centroE.T.S.I. Informáticaes_ES


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