An Improved Quantum-Behaved Particle Swarm Optimization with Binary Encoding

Based on the discussing of Quantum-Behaved Particle Swarm Optimization with Binary Encoding (BQPSO) , changed parameter is introduced into algorithm to make the progress of evolution more reasonable ,and multi-point crossover operator is used in computing the coordinate of the local attractor to increasing the diversity of populations and improve the global searching ability ,a modified BQPSO algorithm is proposed. The new algorithm shows better performance than BPSO and BQPSO algorithms in solving test functions.