{"id":32346,"date":"1997-01-01T00:00:00","date_gmt":"1997-01-01T00:00:00","guid":{"rendered":"https:\/\/www.deberes.net\/tesis\/sin-categoria\/ode-un-nuevo-modelo-neuronal-estocastico-para-optimizacion-combinatoria\/"},"modified":"1997-01-01T00:00:00","modified_gmt":"1997-01-01T00:00:00","slug":"ode-un-nuevo-modelo-neuronal-estocastico-para-optimizacion-combinatoria","status":"publish","type":"post","link":"https:\/\/www.deberes.net\/tesis\/matematicas\/ode-un-nuevo-modelo-neuronal-estocastico-para-optimizacion-combinatoria\/","title":{"rendered":"Ode: un nuevo modelo neuronal estocastico para optimizacion combinatoria."},"content":{"rendered":"<h2>Tesis doctoral de <strong> Jos\u00e9 Fernando Diaz Martin <\/strong><\/h2>\n<p>Esta tesis se enmarca dentro del area de redes neuronales artificiales y optimizacion combinatoria, y tiene como objetivo el desarrollo de nuevas tecnicas de optimizacion basadas en modelos neuronales, que sean capaces de resolver problemas practicos de dimension real, obteniendo soluciones de alta calidad en tiempos de ejecucion factibles. Siguiendo la aproximacion general para la construccion de un sistema conexionista, se define un modelo teorico general apropiado para problemas de optimizacion combinatoria, analizandose tanto su arquitectura o estructura estatica como su comportamiento dinamico (modo de operacion y estabilidad). El estudio practico del modelo propuesto se realiza sobre tres problemas clasicos de optimizacion combinatoria: el problema del viajante comercial, pvc, el problema de la particion de grafos, ppg, y el problema de la asignacion cuadratica, pac, evaluando el sistema con respecto a su complejidad temporal y a la calidad de las soluciones obtenidas. Finalmente, se hace una descripcion de la aplicacion practica que se ha desarrollado sobre una importante area de interes en el entorno de fabricacion industrial: neuroprog, un programador predictivo para sistemas de produccion discreta.<\/p>\n<p>&nbsp;<\/p>\n<h3>Datos acad\u00e9micos de la tesis doctoral \u00ab<strong>Ode: un nuevo modelo neuronal estocastico para optimizacion combinatoria.<\/strong>\u00ab<\/h3>\n<ul>\n<li><strong>T\u00edtulo de la tesis:<\/strong>\u00a0 Ode: un nuevo modelo neuronal estocastico para optimizacion combinatoria. <\/li>\n<li><strong>Autor:<\/strong>\u00a0 Jos\u00e9 Fernando Diaz Martin <\/li>\n<li><strong>Universidad:<\/strong>\u00a0 Deusto<\/li>\n<li><strong>Fecha de lectura de la tesis:<\/strong>\u00a0 01\/01\/1997<\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<h3>Direcci\u00f3n y tribunal<\/h3>\n<ul>\n<li><strong>Director de la tesis<\/strong>\n<ul>\n<li>Veronica Canivell Castillo<\/li>\n<\/ul>\n<\/li>\n<li><strong>Tribunal<\/strong>\n<ul>\n<li>Presidente del tribunal: Francisco Javier Zubillaga Zubimendi <\/li>\n<li> Gutierrez Lopez Jos\u00e9 Antonio (vocal)<\/li>\n<li>Juan Rios Carrion (vocal)<\/li>\n<li>Anselmo Del Moral Bueno (vocal)<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Tesis doctoral de Jos\u00e9 Fernando Diaz Martin Esta tesis se enmarca dentro del area de redes neuronales artificiales y optimizacion [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center 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