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dc.contributor.authorMartínez Vega, Daniel
dc.date.accessioned2018-12-03T20:21:07Z
dc.date.available2018-12-03T20:21:07Z
dc.date.issued2018-01-11
dc.identifier.isbn978-3-319-71008-2es_MX
dc.identifier.isbn978-3-319-71007-5es_MX
dc.identifier.urihttp://cathi.uacj.mx/20.500.11961/4371
dc.description.abstractThe problems of the real world, within which the variable time is present, have involved continuous changes. These problems usually change over time in their objectives, constraints or parameters. Therefore, it is necessary to carry out a readjustment when calculating their solution. This paper proposes an original way of approaching the project portfolio selection problem enriched with dynamic allocation of resources. A new mathematical model is proposed formulating this multi-objective optimization problem, as well as its exact and approximate solution, the latter based on four of the algorithms that in our opinion stand out in the state of the art: Archive-Based hybrid Scatter Search, MultiObjective Cellular, Nondominated Sorting Genetic Algorithm II and Strength Pareto Evolutionary Algorithm 2. We experimentally demonstrate the benefits of our proposal and leave open the possibility that its study will apply to large-scale problems.es_MX
dc.description.urihttps://link.springer.com/chapter/10.1007/978-3-319-71008-2_26es_MX
dc.language.isoenes_MX
dc.publisherSpringeres_MX
dc.relation.ispartofProducto de investigación IITes_MX
dc.relation.ispartofInstituto de Ingeniería y Tecnologíaes_MX
dc.subjectDynamic allocation of resourceses_MX
dc.subjectMultiobjective Optimization Problemses_MX
dc.subject.otherinfo:eu-repo/classification/cti/1es_MX
dc.titleModeling and project portfolio selection problem enriched with dynamic allocation of resourceses_MX
dc.typeCapítulo de libroes_MX
dcterms.thumbnailhttp://ri.uacj.mx/vufind/thumbnails/rupiiit.pnges_MX
dcrupi.institutoInstituto de Ingeniería y Tecnologíaes_MX
dcrupi.cosechableSies_MX
dcrupi.subtipoInvestigaciónes_MX
dcrupi.nopagina365-378es_MX
dcrupi.alcanceInternacionales_MX
dcrupi.paisSwitzerlandes_MX
dc.identifier.doidoi.org/10.1007/978-3-319-71008-2_26es_MX
dc.contributor.coauthorRivera-Zárate, Gilberto
dc.lgacOPTIMIZACIÓN INTELIGENTEes_MX
dc.cuerpoacademicoInteligencia Artificial Aplicadaes_MX
dcrupi.titulolibroFuzzy Logic Augmentation of Neural and Optimization Algorithms: Theoretical Aspects and Real Applicationses_MX


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