International Conference on Instrumentation, Measurement, Circuits and Systems (ICIMCS 2011)
273 An Improved Quantum-Behaved Particle Optimization with Differential Evolution
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Quantum particle swarm optimization, as a random search algorithm having quantum behavior based on the classical particle swarm optimization, , with is more powerful and less control over search parameters compared to particle swarm optimization. But each of the algorithms is easily trapped in local optimal value resulting prematurity. This article aims to increase diversity in search of particles, proposes a method to improve the QPSO by differential evolution and shows that the algorithm is superiority compared to particle swarm optimization and quantum particle swarm optimization by standard test functions.