A Chaos Quantumbehaved Particle Swarm Optimization #br#
Algorithm Based on Differential Evolution

doi:10.3969/j.issn.1006-2475.2017.08.005

Abstract

Abstract:

In view of the shortcomings of the quantumbehaved particle swarm optimization algorithm that is prone to premature convergence to the local optimal solution, this

paper proposed a chaos quantumbehaved particle swarm algorithm based on differential evolution. In order to enhance the diversity of the particles, the chaotic sequences of

Logistic maps are introduced into the particle in this algorithm. Then, the crossover and mutation operation is performed for the premature particles which can avoid the local

optimum in the latter part of the particle. Experimental results show that the proposed algorithm has faster convergence speed and better convergence performance than quantum

particle swarm algorithm.


Key words: quantum behaved particle swarm optimization, differential evolution, chaos

CLC Number:

TP301.6

WANG Zhi. A Chaos Quantumbehaved Particle Swarm Optimization #br# Algorithm Based on Differential Evolution[J]. Computer and Modernization, 2017, 0(8): 22-.

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A Chaos Quantumbehaved Particle Swarm Optimization #br# Algorithm Based on Differential Evolution

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