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针对量子行为的粒子群优化(QPSO)算法存在早熟收敛的缺点,首先结合选择操作,提出2种改进的QPSO算法:基于锦标赛选择的QPSO算法和基于轮盘赌选择的QPSO算法,并施加到全局最优位置,以提高算法的搜索能力;然后证明了此算法的全局收敛性.典型标准函数优化的仿真结果表明,该算法具有较强的全局搜索能力.
QPSO algorithm for quantum behavior has the shortcomings of premature convergence. Firstly, two improved QPSO algorithms are proposed based on the selection operation: QPSO algorithm based on tournament selection and QPSO algorithm based on roulette selection, and applied to the global The optimal location to improve the search ability of the algorithm, and then prove the global convergence of the algorithm.The simulation results of the typical standard function show that the algorithm has a strong global search ability.