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| Quantum Cooperative Immune Algorithm for Dynamic Optimization Problem |
| WU Qiu-Yi, JIAO Li-Cheng, WEI Jun, LI Yang-Yang |
| Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China,Institute of Intelligent Information Processing, Xidian University, Xi'an 710071 |
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Abstract A quantum cooperative immune algorithm is proposed for dynamic optimization problem, which is based on the synergism strategy and principles of quantum-inspired immune computing, and its global convergence is proved in theory. Individuals in a population are represented by quantum bits(qubits).In the individual's updating, the quantum rotation gate strategy and the dynamic adjusting rotation angle mechanism are applied to accelerate convergence. By using cooperative strategy, the information between the subpopulations is exchanged and the diversity of the population is improved. The stability of the proposed algorithm is strengthened to make it fit for the dynamic problem by introducing the relevance of quantum population. In the experiment, the quantum cooperative immune algorithm is tested on dynamic problem and compared with other algorithms by t test. The results indicate that the proposed algorithm has good robustness and adaptability.
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Received: 08 September 2008
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2009, Vol. 22 
