一种求解高维复杂函数优化问题的混合粒子群优化算法

对于高维复杂函数,传统的确定性算法易陷入局部最小,而单一的全局随机搜索算法收敛速度慢.本文通过将粒子群优化算法和单纯形法相结合,利用前者搜索速度快、搜索范围广和后者收敛速度快的特 性,提出一种快速、易实现的混合粒子群优化算法.基于典型高维复杂函数的仿真表明:该混合算法效率高、优化性能好、对初值具有很强的鲁棒性,其性能大大优于单一的优化方法.

A Hybrid Particle Swarm Optimization Algorithm for Solving Complex Functions with High Dimensions

For complex functions with high dimensions, canonical optimization methods are easy to be trapped in local minima and simple random search methods are slow on convergence. This paper proposes an effective hybrid optimization which combines particle swarm optimization with simple method, and it adopts quick and broad searching of the former, and quick convergence of the latter simultaneously. Simulation results on benchmark complex functions with high dimensions show that the hybrid algorithm is effective, efficient and fairly robust to initial conditions. The performance of the hybrid algorithm excels those of single optimization methods.