基于单纯形法的量子粒子群优化算法

针对粒子群优化算法容易陷入局部极值点,进化后期收敛慢和优化精度较差等缺点,提出了将单纯形搜索法与量子粒子群算法混合的改进算法,更好的平衡了全局搜索和局部搜索能力.仿真结果表明,该算法效率高、优化性能好,其性能远远优于一般的粒子群算法与量子粒子群算法.

Quantum_ Behaved Particle Swarm Optimization Algorithm Based on Simplex Method

In allusion to particle swarm optimization algorithm (PSO) many defects such as being easy to get into local ex-tremum, slow convergence in the end of evolution stage and low computational precision. A quantum_ behaved particle swarm optimization algorithm (QPSO) with simplex method (SQPSO) is proposed, which can better balance the global searching and local searching ability. The experiment result demonstrated that SQPSO is of high efficiency, and of excel-lent optimum performance, It is of much better performance to PSO and QPSO.