Aplicación de métodos heurísticos en la solución de problemas de configuración
Fecha
2007-06-18
Autores
Martínez Jiménez, Yailen
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Editor
Universidad Central “Marta Abreu” de Las Villas
Resumen
El objetivo general de la investigación consiste en el desarrollo de algoritmos para la solución de
problemas de configuración utilizando un modelo de razonamiento funcional.
En el contenido del trabajo se expone el marco teórico-referencial de la investigación, enfatizando
en los modelos existentes para resolver este tipo de problema, así como la ausencia de aplicación de
métodos heurísticos en este campo, donde las características del problema, que es minimizar la
cantidad de componentes que aparecen en la solución, hace necesario su uso cuando la complejidad
del problema aumenta.
Es por esto que se estudia la aplicación de tres métodos heurísticos, Ascensión de Colinas,
Algoritmos Genéticos y Sistema de Colonias de Hormigas, los cuales fueron modelados de acuerdo
a las características del problema a resolver y su desempeño fue probado usando diferentes bases de
datos de prueba. Se realizó un análisis de los parámetros a utilizar en cada caso, analizando distintas
variantes de ejecución.
El estudio comparativo realizado con las distintas soluciones encontradas por cada uno de los
algoritmos propuestos arrojó que los mejores resultados son obtenidos en todos los casos por el
algoritmo Sistema de Colonias de Hormigas, perteneciente a la metaheurística Optimización basada
en Colonias de Hormigas.
The major goal of this research project is the development of algorithms for the solution of configuration problems by utilizing a functional reasoning model. The contents of this document clearly exhibit the theoretical-referential framework of the research conducted, stressing on the existing models for solving this sort of problems as well as the lack of application of heuristic methods in the aforementioned field, wherein the problem’s essentials (minimizing the number of components that make up the solution) makes indispensable their use as the problem’s complexity rises. For such reason, three heuristic methods (Hill Climbing, Genetic Algorithms and Ant Colony System) are brought up and carefully applied and fashioned according to the features of the problem to be solved. Their performance was tested by means of several test data bases. A survey on how to set up the parameters of each algorithm is included in the research work. As an outcome of the comparative study carried out between the different solutions found by each of the suggested algorithms, it has been shown that the best results are attained in all cases by the Ant Colony System procedure, belonging to the Ant Colony Optimization metaheuristic.
The major goal of this research project is the development of algorithms for the solution of configuration problems by utilizing a functional reasoning model. The contents of this document clearly exhibit the theoretical-referential framework of the research conducted, stressing on the existing models for solving this sort of problems as well as the lack of application of heuristic methods in the aforementioned field, wherein the problem’s essentials (minimizing the number of components that make up the solution) makes indispensable their use as the problem’s complexity rises. For such reason, three heuristic methods (Hill Climbing, Genetic Algorithms and Ant Colony System) are brought up and carefully applied and fashioned according to the features of the problem to be solved. Their performance was tested by means of several test data bases. A survey on how to set up the parameters of each algorithm is included in the research work. As an outcome of the comparative study carried out between the different solutions found by each of the suggested algorithms, it has been shown that the best results are attained in all cases by the Ant Colony System procedure, belonging to the Ant Colony Optimization metaheuristic.
Descripción
Palabras clave
Métodos Heurísticos, Solución de Problemas, Configuración, Razonamiento Funcional, Desarrollo de Algoritmos