An Improved Algorithm of Quantum Particle Swarm Optimization
Jing Jin · Journal of Software · 2014
Based on the classical particle optimization algorithm and the quantum behavioral theory, this paper proposes an improved QPSO algorithm---GLQPSO to perfect the global and local convergence speed ability and speed of classical particle swarm. To achieve this purpose, the author introduces an improved Logistic chaotic mapping theory [1] to conduct chaotic search for the initial particle and chaotic remolding of the locally optimized particle swarm. The test of the classical function has proved the success of this effort.