The performance of some meta-heuristics in continuous problems studied according to the location of the optima in the search space
Many hard optimization problems can only be effectively handled by meta-heuristic methods. Some continuous optimization problems have specifi c characteristics that demand a particular interest. These features include the location of the optima in a specifi c region of search space. Hence the main g...
- Autores:
-
Navarro, Ricardo
Puris, Amilkar
Bello, Rafael
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2013
- Institución:
- Universidad Nacional de Colombia
- Repositorio:
- Universidad Nacional de Colombia
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.unal.edu.co:unal/73151
- Acceso en línea:
- https://repositorio.unal.edu.co/handle/unal/73151
http://bdigital.unal.edu.co/37626/
- Palabra clave:
- continuous optimization
meta-heuristic
search space bounds
- Rights
- openAccess
- License
- Atribución-NoComercial 4.0 Internacional
| Summary: | Many hard optimization problems can only be effectively handled by meta-heuristic methods. Some continuous optimization problems have specifi c characteristics that demand a particular interest. These features include the location of the optima in a specifi c region of search space. Hence the main goal of this paper is assessing the performance of some outstanding population-based meta-heuristics on functions with optima on bounds and problems with optima off bounds. It is studied by taking a set of benchmark functions from the fi eld of optimization as a point of departure. |
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