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dc.contributor.author | Yepes Piqueras, Víctor![]() |
es_ES |
dc.contributor.author | Martí Albiñana, José Vicente![]() |
es_ES |
dc.date.accessioned | 2015-04-17T08:41:30Z | |
dc.date.available | 2015-04-17T08:41:30Z | |
dc.date.issued | 2015-01 | |
dc.identifier.issn | 0926-5805 | |
dc.identifier.uri | http://hdl.handle.net/10251/48918 | |
dc.description.abstract | This paper describes a methodology to optimize cost and CO2 emissions when designing precast-prestressed concrete road bridges with a double U-shape cross-section. To this end, a hybrid glowworm swarm optimization algorithm (SAGSO) is used to combine the synergy effect of the local search with simulated annealing (SA) and the global search with glowworm swarm optimization (GSO). The solution is defined by 40 variables, including the geometry, materials and reinforcement of the beam and the slab. Regarding the material, high strength concrete is used as well as self-compacting concrete in beams. Results provide engineers with useful guidelines to design PC precast bridges. The analysis also revealed that reducing costs by 1 Euro can save up to 1.75 kg in CO2 emissions. Finally, the parametric study indicates that optimal solutions in terms of monetary costs have quite a satisfactory environmental outcome and differ only slightly from the best possible environmental solution obtained. (C) 2014 Elsevier B.V. All rights reserved. | es_ES |
dc.description.sponsorship | This study was funded by the Spanish Ministry of Science and Innovation (Research Project BIA2011-23602) and by the Universitat Politecnica de Valencia (Research Project SP20120341). The authors are grateful to the anonymous reviewers for their constructive comments and useful suggestions. The authors are also grateful to Dr. Debra Westall for her thorough revision of the manuscript | en_EN |
dc.language | Inglés | es_ES |
dc.publisher | Elsevier | es_ES |
dc.relation.ispartof | Automation in Construction | es_ES |
dc.rights | Reserva de todos los derechos | es_ES |
dc.subject | Optimization | es_ES |
dc.subject | Glowworm swarm algorithm | es_ES |
dc.subject | Computer aided design | es_ES |
dc.subject | Structural design | es_ES |
dc.subject | Sustainable design | es_ES |
dc.subject | Precast concrete | es_ES |
dc.subject | Bridges | es_ES |
dc.subject.classification | INGENIERIA DE LA CONSTRUCCION | es_ES |
dc.title | Cost and CO2 emission optimization of precast prestressed concrete U-beam road bridges by a hybrid glowworm swarm algorithm | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.1016/j.autcon.2014.10.013 | |
dc.relation.projectID | info:eu-repo/grantAgreement/MICINN//BIA2011-23602/ES/DISEÑO EFICIENTE DE ESTRUCTURAS CON HORMIGONES NO CONVENCIONALES BASADOS EN CRITERIOS SOSTENIBLES MULTIOBJETIVO MEDIANTE EL EMPLEO DE TECNICAS DE MINERIA DE DATOS/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/UPV//SP20120341/ | es_ES |
dc.rights.accessRights | Abierto | 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. Instituto de Ciencia y Tecnología del Hormigón - Institut de Ciència i Tecnologia del Formigó | es_ES |
dc.description.bibliographicCitation | Yepes Piqueras, V.; Martí Albiñana, JV. (2015). Cost and CO2 emission optimization of precast prestressed concrete U-beam road bridges by a hybrid glowworm swarm algorithm. Automation in Construction. 49:123-134. https://doi.org/10.1016/j.autcon.2014.10.013 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | http://dx.doi.org/10.1016/j.autcon.2014.10.013 | es_ES |
dc.description.upvformatpinicio | 123 | es_ES |
dc.description.upvformatpfin | 134 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 49 | es_ES |
dc.relation.senia | 280045 | |
dc.contributor.funder | Ministerio de Ciencia e Innovación | es_ES |
dc.contributor.funder | Universitat Politècnica de València | es_ES |