2005•Unpublished venueRequires access

Particle Swarm Optimization Algorithm and Comparison with Genetic Algorithm

Tianxiang Gu

Abstract

Particle swarm optimization, rooting from simulation of swarm of bird, solves optimization problem. Firstly, discusses particle swarm optimization algorithm principle and step of implementation, and then analyzes each of parameter. Particle swarm optimization algorithm compares with genetic algorithm through the same mathematic function. The comparative result indicates that Particle swarm optimization algorithm can obtain the optimum solutions more easily than genetic algorithm and it is a good optimization method with strong competition.

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Available abstract

Key concepts: Meta-optimization, Multi-swarm optimization, Particle swarm optimization, Imperialist competitive algorithm, Metaheuristic, Derivative-free optimization, Algorithm, Mathematical optimization