Towards Applying River Formation Dynamics in Continuous Optimization Problems
River Formation Dynamics (RFD) is a metaheuristic that has been successfully used by different research groups to deal with a wide variety of discrete combinatorial optimization problems. However, no attempt has been done to adapt it to continuous optimization domains. In this paper we propose a fir...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2019 |
| País: | España |
| Institución: | Universidad Complutense de Madrid (UCM) |
| Repositorio: | Docta Complutense |
| Idioma: | inglés |
| OAI Identifier: | oai:docta.ucm.es:20.500.14352/12830 |
| Acceso en línea: | https://hdl.handle.net/20.500.14352/12830 |
| Access Level: | acceso abierto |
| Palabra clave: | Swarm Intelligence Metaheuristics Optimization River Formation Dynamics Inteligencia artificial (Informática) Programación de ordenadores (Informática) Software 1203.04 Inteligencia Artificial 1203.23 Lenguajes de Programación 3304.16 Diseño Lógico |
| Sumario: | River Formation Dynamics (RFD) is a metaheuristic that has been successfully used by different research groups to deal with a wide variety of discrete combinatorial optimization problems. However, no attempt has been done to adapt it to continuous optimization domains. In this paper we propose a first approach to obtain such objective, and we evaluate its usefulness by comparing RFD results against those obtained by other more mature metaheuristics for continuous domains. In particular, we compare with the results obtained by Particle Swarm Optimization, Artificial Bee Colony, Firefly Algorithm, and Social Spider Optimization. |
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