通过引入量子行为来增强粒子的全局收敛能力,提出了量子粒子群优化算法(QPSO),并用于求解整数规划问题。测试函数的仿真结果表明,通过适当的参数设置,并将每次迭代所生成的实数值截至整数值后进行下一次迭代,可以保证QPSO算法求解的精度,提高收敛速度且能有效避免早熟。
The performance of Quantum-behaved PSO for integer programming on several test functions was investigated. PSO and Quantum-behaved PSO were firstly tested with different intervals of parameter to and β to attain a proper variant setting respectively. Then with the proper setting, the experimental results indicated that QPSO handles integer programming problems much efficiently, and in most cases it converged faster than the PSO algorithm.