摘要
针对离散空间优化问题,给出二进制编码的量子粒子群优化(BQPSO)算法的设计思路,重新定义粒子的位置矢量和粒子之间的距离,提出了BQPSO算法的进化方程.通过泛函分析的方法分析了BQPSO算法的收敛性,得出全局收敛的结论,并通过多个测试函数测试了BQPSO算法的性能.求解结果验证了算法的优越性.
The thought of quantum-behaved particle swarm optimization with binary encoding （BQPSO） is discussed,and evolution equations are given which are completely different from the QPSO algorithm.Position vector and distance between two positions are redefined,and QPSO algorithm with binary encoding is proposed.The convergence of BQPSO algorithm is analyzed by using functional analysis method,and conclusion of global convergence is derived.The test result for BQPSO algorithm shows its better performance in solving test functions.
出处
《控制与决策》
EI
CSCD
北大核心
2010年第1期99-104,共6页
Control and Decision
基金
国家自然科学基金项目(60474030)
