A Chaos Quantum Immune Algorithm for Continuous Space Optimization
LI Pan-Chi1,2, LI Shi-Yong1
1.Department of Control Science and Engineering, Harbin Institute of Technology, Harbin 150001 2.Department of Computer Science, Daqing Petroleum Institute, Daqing 163318
Abstract By integrating the ergodicity of chaos searching and the high efficiency of quantum computation into immune optimization, a novel chaos quantum immune algorithm for continuous space optimization is presented. In this algorithm, antibodies in colonies are coded by quantum bits and updated by quantum rotation gates. To change phase of qubit, two different chaos variables are introduced into the quantum rotation gate. The one with the relatively small amplitude performs the cloning of excellent individuals to implement the local searching, and the other one with the relatively large amplitude performs the mutation of inferior individuals to realize the global searching. The convergence of the proposed algorithm has been proved. The experimental results indicate that the algorithm remarkably improves the convergence performance and the search efficiency of the immune optimization algorithm.
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2007, Vol. 20 
