| Revue: | Computación y sistemas |
| Base de datos: | PERIÓDICA |
| Número de sistema: | 000376145 |
| ISSN: | 1405-5546 |
| Autores: | Velasco, Jonás1 Saucedo Espinosa, Mario A1 Escalante, Hugo Jair2 Mendoza, Karlo1 Villarreal Rodríguez, César Emilio1 Chacón Mondragón, Oscar L1 Berrones, Arturo1 |
| Instituciones: | 1Universidad Autónoma de Nuevo León, Facultad de Ingeniería Mecánica y Eléctrica, Monterrey, Nuevo León. México 2Instituto Nacional de Astrofísica, Optica y Electrónica, Departamento de Ciencias Computacionales, Tonantzintla, Puebla. México |
| Año: | 2014 |
| Periodo: | Abr-Jun |
| Volumen: | 18 |
| Número: | 2 |
| Paginación: | 243-257 |
| País: | México |
| Idioma: | Inglés |
| Tipo de documento: | Artículo |
| Enfoque: | Experimental, aplicado |
| Resumen en inglés | Adaptive Gibbs Sampling (AGS) algorithm is a new heuristic for unconstrained global optimization. AGS algorithm is a population-based method that uses a random search strategy to generate a set of new potential solutions. Random search combines the one-dimensional Metropolis-Hastings algorithm with the multidimensional Gibbs sampler in such a way that the noise level can be adaptively controlled according to the landscape providing a good balance between exploration and exploitation over all search space. Local search strategies can be coupled to the random search methods in order to intensify in the promising regions. We have performed experiments on three well known test problems in a range of dimensions with a resulting testbed of 33 instances. We compare the AGS algorithm against two deterministic methods and three stochastic methods. Results show that the AGS algorithm is robust in problems that involve central aspects which is the main reason of global optimization problem difficulty including high-dimensionality, multi-modality and non-smoothness |
| Disciplinas: | Ciencias de la computación |
| Palabras clave: | Procesamiento de datos, Búsqueda al azar, Heurística, Optimización global, Algoritmo Metropolis-Hastings |
| Keyword: | Computer science, Data processing, Random search, Heuristics, Global optimization, Metropolis-Hastings algorithm |
| Texte intégral: | Texto completo (Ver HTML) |
