A Binary Quantum-behaved Particle Swarm Optimization Algorithm with Cooperative Approach
A novel binary Quantum-behaved Particle Swarm Optimization algorithm with cooperative approach (CBQPSO) is introduced. In the proposed algorithm, the updating method of particles previous best position and swarms global best position are performed in each dimension of solution vector to avoid loss some components that have moved closer to the global optimal solution in the vector. Five test functions are used to test the performance of CBQPSO. The results of experiments show that the proposed technique can increase diversity of population and converge more rapidly than other binary algorithms.
Keywords: Quantum-behaved Particle Swarm Optimization, Binary, Cooperative Approach, Test Functions.
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ABOUT THE AUTHOR
Jing Zhao
1School of Digital Media, Jiangnan University Wuxi, 214122, Jiangsu, China 2School of Information, Shandong Polytechnic University,Jinan, 250353, Shandong, China
Jing Zhao
1School of Digital Media, Jiangnan University Wuxi, 214122, Jiangsu, China 2School of Information, Shandong Polytechnic University,Jinan, 250353, Shandong, China
