量子协同免疫动态优化算法

基于协同策略和量子免疫计算理论,提出量子协同免疫动态优化算法,并从理论上证明算法的全局收敛性.该算法采用量子比特编码表达种群中的抗体,并采用量子旋转门和动态调整旋转步长策略来演化抗体,加速原有克隆算子的收敛.该算法中引入协同策略增强子群体间的信息交流,提高种群的多样性,同时利用量子编码种群的关联性,使算法具有更强的稳定性,能够较好地适应于动态问题的求解.文中通过一系列动态背包测试问题和交叉验证(t检验)实验表明,量子协同免疫动态优化算法具有更强的鲁棒性和适应性,显示出较优越的性能.

Quantum Cooperative Immune Algorithm for Dynamic Optimization Problem

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 subpepulations 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.