结合Hooke-Jeeves和粒子群的优点,提出了一种混合粒子群算法,用于求解非线性方程组,以克服Hooke-Jeeves算法对初始值敏感和粒子群容易陷入局部极值而导致解的精度不够的缺陷。该算法充分发挥了粒子群强大的全局搜索能力和Hooke-Jeeves的局部精细搜索能力,数值实验结果表明:能够以满意的精度求出对未知数具有敏感性的非线性方程组的解,具有良好的鲁棒性和较快的收敛速度和较高的搜索精度。
A Hybrid Particle Swarm Optimization(HPSO) algorithm,which combines the advantages of the method HookeJeeves(HJ) and Particle Swarm Optimization(PSO),is put forward to solve systems of nonlinear functions,and it can be used to overcome the difficulty in selecting good initial guess for HJ and inaccuracy of PSO due to being easily trapped into local optimal.The algorithm has sufficiently displayed the performance of PSO’s global search and HJ’s accurate local search.Numerical computations show that the approach has great robustness,high convergence rate and precision,and it can give satisfactory solutions.