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Campo DC | Valor | Lengua/Idioma |
---|---|---|
dc.contributor.advisor | Godoy del Campo, Julio | es |
dc.contributor.advisor | Asín Achá, Roberto | es |
dc.contributor.author | Pezo Vergara, Catalina | es |
dc.date.accessioned | 2023-11-30T10:24:20Z | - |
dc.date.available | 2023-11-30T10:24:20Z | - |
dc.date.issued | 2023 | - |
dc.identifier.uri | http://repositorio.udec.cl/jspui/handle/11594/11588 | - |
dc.description | Tesis presentada para optar al grado de Magíster en Ciencias de la Computación. | es |
dc.description.abstract | Machine learning (ML) techniques have been proposed to automatically select the best solver from a portfolio of solvers, based on predicted performance. These techniques have been applied to various problems, such as Boolean Satisfiability, Traveling Salesperson, Graph Coloring, and others. These methods, known as meta-solvers, take an instance of a problem and a portfolio of solvers as input, then predict the best-performing solver and execute it to deliver a solution. Typically, the quality of the solution improves with a longer computational time. This has led to the development of anytime selectors, which consider both the instance and a user-prescribed computational time limit. Anytime meta-solvers predict the best-performing solver within the specified time limit. In this study, we focus on the task of designing anytime meta-solvers for the NP-hard optimization problem of Pseudo-Boolean Optimization (PBO). The effectiveness of our approach is demonstrated via extensive empirical study in which our anytime meta-solver improves dramatically on the performance of Mixed Integer Programming solver Gurobi, the best-performing single solver in the portfolio. | en |
dc.language.iso | en | en |
dc.publisher | Universidad de Concepción | es |
dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/4.0/?ref=chooser-v1 | en |
dc.title | Anytime automatic algorithm selection for the Pseudo-Boolean Optimization problem. | es |
dc.type | Tesis | es |
dc.description.facultad | Facultad de Ingeniería. | es |
dc.description.departamento | Departamento Ingeniería Informática y Ciencias de la Computación | es |
dc.description.campus | Concepción. | es |
Aparece en las colecciones: | Ingeniería Informática y Ciencias de la Computación - Tesis Magister |
Ficheros en este ítem:
Fichero | Descripción | Tamaño | Formato | |
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Pezo Vergara_Catalina Tesis.pdf | 1,96 MB | Adobe PDF | Visualizar/Abrir |
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