Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/113634
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dc.contributor.authorGreiner Sánchez, David Juanen_US
dc.contributor.authorPeriaux, Jacquesen_US
dc.contributor.authorEmperador Alzola, José Maríaen_US
dc.contributor.authorGalván González, Blas Joséen_US
dc.date.accessioned2022-02-03T11:23:01Z-
dc.date.available2022-02-03T11:23:01Z-
dc.date.issued2019en_US
dc.identifier.urihttp://hdl.handle.net/10553/113634-
dc.description.abstractAmong the advances in meta heuristics and evolutionary algorithms for engineering design and optimization [1], their hybridization with game strategies has been shown in recent years as a methodology to improve performance and results of the optimum design procedure in computational engineering, particularly in aeronautical engineering and CFD problems [2], as well as in structural engineering problems [3]. In this study, we handle the use of virtual Nash genetic algorithms (Nash GAs) to speed up the optimization search. The minimum constrained weight optimization problem (taking into account constraints of allowable stresses and displacements) of high interest in structural engineering practice, is solved using a game-theory based Nash genetic algorithm (Nash GAs). This procedure performance is applied on different sets of variable splitting of the problem on two test case problems consisting of a discrete sizing cross-section types 55-member and 105-member skeletal steel structures (frame type) and compared with a standard panmictic genetic algorithm. Numerical results of this approach of the structural test case indicate that a significant increase of performance can be achieved using the Nash strategy, both with significant advantages in algorithm robustness in finding the optimum design solution, and in convergence speed-up, illustrating the potential of Nash games for other complex engineering problems. Advantage of the Nash optimization approach is enhanced with the increment of the problem size.en_US
dc.languageengen_US
dc.subject1206 Análisis numéricoen_US
dc.subject330532 Ingeniería de estructurasen_US
dc.subject.otherOptimización numérica, Algoritmos Nashen_US
dc.titleA Study about Problem Size Influence in the Minimization of Constrained Weight of Skeletal Structures with Nash Genetic Algorithmsen_US
dc.typeinfo:eu-repo/semantics/conferenceobjecten_US
dc.typeConferenceObjecten_US
dc.relation.conferenceVIII International Conference on Coupled Problems in Science and Engineering (COUPLED-2019), Sitges, Spainen_US
dc.identifier.urlhttps://congress.cimne.com/coupled2019/admin/files/fileabstract/a425.pdf-
dc.relation.volume8en_US
dc.investigacionIngeniería y Arquitecturaen_US
dc.type2Actas de congresosen_US
dc.utils.revisionen_US
dc.date.coverdateJunio 2019en_US
dc.identifier.ulpgcen_US
dc.contributor.buulpgcBU-INGen_US
item.fulltextCon texto completo-
item.grantfulltextopen-
crisitem.author.deptGIR SIANI: Computación Evolutiva y Aplicaciones-
crisitem.author.deptIU Sistemas Inteligentes y Aplicaciones Numéricas-
crisitem.author.deptDepartamento de Ingeniería Civil-
crisitem.author.deptGIR SIANI: Modelización y Simulación Computacional-
crisitem.author.deptIU Sistemas Inteligentes y Aplicaciones Numéricas-
crisitem.author.deptDepartamento de Ingeniería Civil-
crisitem.author.deptGIR SIANI: Computación Evolutiva y Aplicaciones-
crisitem.author.deptIU Sistemas Inteligentes y Aplicaciones Numéricas-
crisitem.author.orcid0000-0002-4132-7144-
crisitem.author.orcid0000-0002-7020-870X-
crisitem.author.parentorgIU Sistemas Inteligentes y Aplicaciones Numéricas-
crisitem.author.parentorgIU Sistemas Inteligentes y Aplicaciones Numéricas-
crisitem.author.parentorgIU Sistemas Inteligentes y Aplicaciones Numéricas-
crisitem.author.fullNameGreiner Sánchez, David Juan-
crisitem.author.fullNameEmperador Alzola, José María-
crisitem.author.fullNameGalván González, Blas José-
Appears in Collections:Actas de congresos
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