{"id":356811,"date":"2026-09-25T12:21:49","date_gmt":"2026-09-25T15:21:49","guid":{"rendered":"https:\/\/www.ing.uc.cl\/industrial-y-sistemas\/?p=356811"},"modified":"2026-09-30T13:25:41","modified_gmt":"2026-09-30T16:25:41","slug":"undergraduate-operations-research-prize","status":"publish","type":"post","link":"https:\/\/www.ing.uc.cl\/industrial-y-sistemas\/2026\/09\/25\/undergraduate-operations-research-prize\/","title":{"rendered":"Estudiante de Ingenier\u00eda UC es finalista de Undergraduate Operations Research Prize"},"content":{"rendered":"

El trabajo de Martin Cooper propone una nueva metodolog\u00eda para la generaci\u00f3n de desigualdades en problemas de optimizaci\u00f3n polin\u00f3mica binaria<\/h4>\n

\"\"<\/p>\n

Mart\u00edn Cooper<\/strong>, estudiante de Ingenier\u00eda UC<\/strong>, fue seleccionado como uno de los ocho finalistas del Undergraduate Operations Research Prize<\/a> de INFORMS 2026<\/a><\/strong>, por su trabajo \u201cBeyond Hand-Derived Inequalities: Decision Diagrams for Cut Generation in Binary Polynomial Optimization<\/a>\u201d<\/em>.<\/strong><\/p>\n

La investigaci\u00f3n fue desarrollada en el marco de un proyecto de investigaci\u00f3n de pregrado (iPre), bajo la supervisi\u00f3n de la profesora del Departamento de Ingenier\u00eda Industrial y de Sistemas UC, Margarita Castro<\/strong>\u00a0y como parte de su proyecto Fondecyt Regular 1261833.<\/strong><\/p>\n

El estudio aborda problemas de optimizaci\u00f3n polin\u00f3mica binaria, una familia de problemas de optimizaci\u00f3n combinatoria que incluye, entre otros casos, el conocido problema Max-Cut.<\/p>\n

Una nueva forma de generar desigualdades<\/h3>\n

Los problemas de optimizaci\u00f3n polin\u00f3mica binaria pueden representarse mediante estructuras matem\u00e1ticas llamadas hipergr\u00e1ficos, que permiten modelar interacciones entre m\u00e1s de dos elementos. Debido a la complejidad de estos problemas, encontrar soluciones de manera eficiente puede ser especialmente desafiante a medida que aumenta el tama\u00f1o de las instancias.<\/p>\n

Una de las herramientas utilizadas para enfrentar esta dificultad son las desigualdades o cuts<\/em>, que permiten fortalecer la formulaci\u00f3n matem\u00e1tica de un problema y facilitar su resoluci\u00f3n computacional. Tradicionalmente, estas desigualdades se han dise\u00f1ado de manera espec\u00edfica para determinadas estructuras, como ciclos o flowers<\/em>.<\/p>\n

El trabajo de Mart\u00edn Cooper propone una alternativa basada en Decision Diagrams (DDs)<\/strong>, estructuras que permiten representar de manera compacta determinadas relaciones dentro del problema. A partir de un soporte o subestructura previamente seleccionada, el m\u00e9todo construye un Decision Diagram capaz de generar autom\u00e1ticamente una desigualdad v\u00e1lida para esa estructura y luego incorporarla al problema original.<\/p>\n

Adem\u00e1s de desarrollar este mecanismo de generaci\u00f3n de desigualdades, la investigaci\u00f3n estudia las propiedades de los Decision Diagrams utilizados. Entre sus resultados te\u00f3ricos se encuentran una representaci\u00f3n compacta espec\u00edfica para estos problemas, una formulaci\u00f3n extendida del conjunto factible y una caracterizaci\u00f3n del ancho de los diagramas mediante antichains<\/em> v\u00e1lidos. El trabajo tambi\u00e9n establece condiciones que permiten certificar cu\u00e1ndo las desigualdades generadas corresponden a facetas del poliedro local.<\/p>\n

Resultados computacionales<\/h3>\n

La metodolog\u00eda fue evaluada en dos conjuntos de problemas de referencia: LABS<\/strong> y VISION<\/strong>.<\/p>\n

En LABS, una de las estrategias desarrolladas logr\u00f3 cerrar hasta un 92,4% de la brecha inicial de la relajaci\u00f3n en el nodo ra\u00edz<\/strong>, utilizando las desigualdades generadas por el m\u00e9todo.<\/p>\n

En el conjunto VISION, una de las configuraciones logr\u00f3 cerrar el 100% de la brecha en el nodo ra\u00edz<\/strong> en las 45 instancias evaluadas. Adem\u00e1s, alcanz\u00f3 un tiempo promedio de resoluci\u00f3n de 5,76 segundos<\/strong>, frente a los 71,79 segundos<\/strong> obtenidos por el procedimiento de referencia utilizado en el estudio.<\/p>\n

Estos resultados muestran el potencial de los Decision Diagrams como herramienta para generar nuevas desigualdades de manera sistem\u00e1tica y contribuir a la resoluci\u00f3n computacional de problemas de optimizaci\u00f3n combinatoria.<\/p>\n

\"\"<\/p>\n

Presentaci\u00f3n en San Francisco<\/h3>\n

Como finalista del Undergraduate Operations Research Prize<\/strong>, Mart\u00edn Cooper presentar\u00e1 su investigaci\u00f3n el pr\u00f3ximo 1 de noviembre<\/strong>\u00a0en el marco del INFORMS Annual Meeting 2026<\/strong>, que se realizar\u00e1 entre el 1 y el 4 de noviembre en San Francisco, Estados Unidos.<\/p>\n

La presentaci\u00f3n ser\u00e1 tambi\u00e9n la instancia en que se dar\u00e1 a conocer al ganador del premio.<\/p>\n","protected":false},"excerpt":{"rendered":"

El trabajo de Martin Cooper propone una nueva metodolog\u00eda para la generaci\u00f3n de desigualdades en problemas de optimizaci\u00f3n polin\u00f3mica binaria Mart\u00edn Cooper, estudiante de Ingenier\u00eda UC, fue seleccionado como uno de los ocho finalistas del Undergraduate Operations Research Prize de INFORMS 2026, por su trabajo \u201cBeyond Hand-Derived Inequalities: Decision Diagrams for Cut Generation in Binary Polynomial Optimization\u201d. La investigaci\u00f3n fue desarrollada en el marco de un proyecto de investigaci\u00f3n de pregrado (iPre), bajo la supervisi\u00f3n de la profesora del Departamento de Ingenier\u00eda Industrial y de Sistemas UC, Margarita Castro\u00a0y como parte de su proyecto Fondecyt Regular 1261833. El estudio aborda problemas de optimizaci\u00f3n polin\u00f3mica binaria, una familia de problemas de optimizaci\u00f3n combinatoria que incluye, entre otros casos, el conocido problema Max-Cut. Una nueva forma de generar desigualdades Los problemas de optimizaci\u00f3n polin\u00f3mica binaria pueden representarse mediante estructuras matem\u00e1ticas llamadas hipergr\u00e1ficos, que permiten modelar interacciones entre m\u00e1s de dos elementos. Debido a la complejidad de estos problemas, encontrar soluciones de manera eficiente puede ser especialmente desafiante a medida que aumenta el tama\u00f1o de las instancias. Una de las herramientas utilizadas para enfrentar esta dificultad son las desigualdades o cuts, que permiten fortalecer la formulaci\u00f3n matem\u00e1tica de un problema y facilitar su resoluci\u00f3n computacional. Tradicionalmente, estas desigualdades se han dise\u00f1ado de manera espec\u00edfica para determinadas estructuras, como ciclos o flowers. El trabajo de Mart\u00edn Cooper propone una alternativa basada en Decision Diagrams (DDs), estructuras que permiten representar de manera compacta determinadas relaciones dentro del problema. A partir de un soporte o subestructura previamente seleccionada, el m\u00e9todo construye un Decision Diagram capaz de generar autom\u00e1ticamente una desigualdad v\u00e1lida para esa estructura y luego incorporarla al problema original. Adem\u00e1s de desarrollar este mecanismo de generaci\u00f3n de desigualdades, la investigaci\u00f3n estudia las propiedades de los Decision Diagrams utilizados. Entre sus resultados te\u00f3ricos se encuentran una representaci\u00f3n compacta espec\u00edfica para estos problemas, una formulaci\u00f3n extendida del conjunto factible y una caracterizaci\u00f3n del ancho de los diagramas mediante antichains v\u00e1lidos. El trabajo tambi\u00e9n establece condiciones que permiten certificar cu\u00e1ndo las desigualdades generadas corresponden a facetas del poliedro local. Resultados computacionales La metodolog\u00eda fue evaluada en dos conjuntos de problemas de referencia: LABS y VISION. En LABS, una de las estrategias desarrolladas logr\u00f3 cerrar hasta un 92,4% de la brecha inicial de la relajaci\u00f3n en el nodo ra\u00edz, utilizando las desigualdades generadas por el m\u00e9todo. En el conjunto VISION, una de las configuraciones logr\u00f3 cerrar el 100% de la brecha en el nodo ra\u00edz en las 45 instancias evaluadas. Adem\u00e1s, alcanz\u00f3 un tiempo promedio de resoluci\u00f3n de 5,76 segundos, frente a los 71,79 segundos obtenidos por el procedimiento de referencia utilizado en el estudio. Estos resultados muestran el potencial de los Decision Diagrams como herramienta para generar nuevas desigualdades de manera sistem\u00e1tica y contribuir a la resoluci\u00f3n computacional de problemas de optimizaci\u00f3n combinatoria. Presentaci\u00f3n en San Francisco Como finalista del Undergraduate Operations Research Prize, Mart\u00edn Cooper presentar\u00e1 su investigaci\u00f3n el pr\u00f3ximo 1 de noviembre\u00a0en el marco del INFORMS Annual Meeting 2026, que se realizar\u00e1 entre el 1 y el 4 de noviembre en San Francisco, Estados Unidos. La presentaci\u00f3n ser\u00e1 tambi\u00e9n la instancia en que se dar\u00e1 a conocer al ganador del premio.<\/p>\n","protected":false},"author":11,"featured_media":356822,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"default","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":"","ast-disable-related-posts":"","theme-transparent-header-meta":"default","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"set","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center 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