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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Detalles Bibliográficos
Autor: ARTURO HERNANDEZ AGUIRRE
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
Descripción
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.