COPSO: Constrained Optimization Via PSO Algorithm
This paper introduces the COPSO algorithm (Constrained Optimization via Particle Swarm Opti- mization) for the solution of single objective constrained optimization problems. The approach includes two new perturbation operators to prevent premature convergence, and a new ring neighborhood struc- tur...
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| Tipo de recurso: | informe técnico |
| Estado: | Versión publicada |
| Fecha de publicación: | 2007 |
| País: | México |
| Institución: | Centro de Investigación en Matemáticas |
| Repositorio: | Repositorio Institucional CIMAT |
| Idioma: | inglés |
| OAI Identifier: | oai:cimat.repositorioinstitucional.mx:1008/632 |
| Acceso en línea: | http://cimat.repositorioinstitucional.mx/jspui/handle/1008/632 |
| Access Level: | acceso abierto |
| Palabra clave: | info:eu-repo/classification/MSC/Optimización info:eu-repo/classification/cti/1 info:eu-repo/classification/cti/12 info:eu-repo/classification/cti/1203 info:eu-repo/classification/cti/120302 |
| Sumario: | This paper introduces the COPSO algorithm (Constrained Optimization via Particle Swarm Opti- mization) for the solution of single objective constrained optimization problems. The approach includes two new perturbation operators to prevent premature convergence, and a new ring neighborhood struc- ture. A constraint handling technique based on feasibility and sum of constraints violation, is equipped with an external Øle to store particles we termed \tolerant" . The goal of the Øle is to extend the life period of those particles that otherwise would be lost after the adjustment of the tolerance of equality constraints. COPSO is applied to various engineering design problems, and for the solution of state of the art benchmark problems. Experiments show that COPSO is robust, competitive and fast. |
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