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The Resource Leveling Problem with multiple resources using an adaptive genetic algorithm

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The Resource Leveling Problem with multiple resources using an adaptive genetic algorithm

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dc.contributor.author Ponz Tienda, José Luis es_ES
dc.contributor.author Yepes Piqueras, Víctor es_ES
dc.contributor.author Pellicer Armiñana, Eugenio es_ES
dc.contributor.author Moreno Flores, Joaquín es_ES
dc.date.accessioned 2014-03-24T08:19:55Z
dc.date.issued 2013-01
dc.identifier.issn 0926-5805
dc.identifier.uri http://hdl.handle.net/10251/36586
dc.description.abstract Resource management ensures that a project is completed on time and at cost, and that its quality is as previously defined; nevertheless, resources are scarce and their use in the activities of the project leads to conflicts in the schedule. Resource Leveling Problems consider how to make the resource consumption as efficient as possible. This paper presents a new Adaptive Genetic Algorithm for the Resource Leveling Problem with multiple resources, and its novelty lies in using the Weibull distribution to establish an estimation of the global optimum as a termination condition. The extension of the project deadline with a penalty is allowed, avoiding the increase in the project criticality punishing the shift of activities. The algorithmis tested with the standard Project Scheduling Problem Library PSPLIB, and a complete analysis and benchmarking test instances are presented. The proposed algorithm is implemented using VBA for Excel 2010 in order to provide a flexible and powerful decision support system that enables practitioners to choose between different feasible solutions to a problem, and in addition it is easily adjustable to the constraints and particular needs of each project in realistic environments. es_ES
dc.description.sponsorship This study was partially funded by the Spanish Ministry of Science and Innovation (research project BIA2011-23602). en_EN
dc.language Inglés es_ES
dc.publisher Elsevier es_ES
dc.relation Spanish Ministry of Science and Innovation (research project BIA2011-23602) es_ES
dc.relation.ispartof Automation in Construction es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Project scheduling es_ES
dc.subject Resource leveling es_ES
dc.subject Genetic algorithms es_ES
dc.subject Benchmarking es_ES
dc.subject.classification CONSTRUCCIONES ARQUITECTONICAS es_ES
dc.subject.classification INGENIERIA DE LA CONSTRUCCION es_ES
dc.subject.classification MATEMATICA APLICADA es_ES
dc.subject.classification PROYECTOS DE INGENIERIA es_ES
dc.title The Resource Leveling Problem with multiple resources using an adaptive genetic algorithm es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1016/j.autcon.2012.10.003
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Construcciones Arquitectónicas - Departament de Construccions Arquitectòniques es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Ingeniería de la Construcción y de Proyectos de Ingeniería Civil - Departament d'Enginyeria de la Construcció i de Projectes d'Enginyeria Civil es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Matemática Aplicada - Departament de Matemàtica Aplicada es_ES
dc.description.bibliographicCitation Ponz Tienda, JL.; Yepes Piqueras, V.; Pellicer Armiñana, E.; Moreno Flores, J. (2013). The Resource Leveling Problem with multiple resources using an adaptive genetic algorithm. Automation in Construction. 29(1):161-172. doi:10.1016/j.autcon.2012.10.003 es_ES
dc.description.accrualMethod Senia es_ES
dc.relation.publisherversion http://dx.doi.org/10.1016/j.autcon.2012.10.003 es_ES
dc.description.upvformatpinicio 161 es_ES
dc.description.upvformatpfin 172 es_ES
dc.type.version info:eu repo/semantics/publishedVersion es_ES
dc.description.volume 29 es_ES
dc.description.issue 1 es_ES
dc.relation.senia 227686


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