Integrated the Simplified Interpolation and Clonal Selection into the Particle Swarm Optimization for Optimization Problems
Particle Swarm Optimization (PSO) is gaining momentum as a simple and effective optimization technique. However, its performance on complex problem with multiple minima falls short of that of the Ant Clony Optimization (ACO) algorithm. The new algorithm, which we call Hybrid Particle Swarm Optimization, combines the ideas of particle swarm optimizati-on with clonal selection strategy and simplified quadratic interpolation (SQI), which is used to improve its local search ability, and to escape from the local optima. Simulation results on 14 benchmark test functions show that the hybrid algorithm is able to avoid the premature convergence and find much better solutions with high speed.
KeywordsParticle Swarm Optimization Clonal Selection Quadratic Interpolation Hybrid Particle Swarm Optimization Clonal Selection Algorithm
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