Title :
Particle evolutionary swarm optimization algorithm (PESO)
Author :
Zavala, Angel E Munoz ; Aguirre, Arturo Hernández ; Diharce, Enrique R Villa
Author_Institution :
Dept. of Comput. Sci., Center for Res. in Math., Guanajuato, Mexico
Abstract :
We introduce the PESO (particle evolutionary swarm optimization) algorithm for solving single objective constrained optimization problems. PESO algorithm proposes two new perturbation operators: "c-perturbation" and "m-perturbation". The goal of these operators is to fight premature convergence and poor diversity issues observed in particle swarm optimization (PSO) implementations. Constraint handling is based on simple feasibility rules. PESO is compared with respect to a highly competitive technique representative of the state-of-the-art in the area using a well-known benchmark for evolutionary constrained optimization. PESO matches most results and outperforms other PSO algorithms.
Keywords :
evolutionary computation; particle swarm optimisation; evolutionary constrained optimization; particle evolutionary swarm optimization algorithm; particle swarm optimization; perturbation operator; premature convergence; Acceleration; Computer science; Constraint optimization; Convergence; Diversity reception; Mathematics; Particle swarm optimization; Process control; Proposals; Space exploration;
Conference_Titel :
Computer Science, 2005. ENC 2005. Sixth Mexican International Conference on
Print_ISBN :
0-7695-2454-0
DOI :
10.1109/ENC.2005.32