混合量子进化算法及其应用

Hybrid Quantum Evolutionary Algorithms and its Application

文章将量子进化算法(QEA)和粒子群算法(PSO)互相结合,提出了两种混合量子进化算法。第一种算法叫做嵌入式粒子群量子进化算法,其主要思想是将简化的PSO进化方程嵌入QEA的进化操作中,简化了QEA算法的结构,增强了QEA跳出局部极值的能力。第二种算法叫做量子二进制粒子群算法,其主要思想是将QEA中的量子染色体的概念引入二进制粒子群算法(BPSO),提高了BPSO算法保持种群多样性的能力和运算速度。通过对0-1背包问题和多用户检测问题的求解表明,新的算法不仅操作更简单,而且全局搜索能力有了显著的提高。

Inspired by the idea of hybrid optimization algorithms,this paper proposes two hybrid Quantum Evolutionary Algorithms（QEA） based on combining QEA with Particle Swarm Optimization（PSO）.The main idea of the first method called PSEQEA is to embed the evolutionary equation of PSO in QEA;while the main idea of the second method called QBPSO is to apply the quantum chromosomes of QEA to binary PSO（BPSO）.The experiment results of the knapsack problem and multiuser detection problem show that the both of the proposed methods not only have simpler algorithm structure,but also perform better than conventional QEA and BPSO in terms of ability of global optimum.