Hybrid Differential Evolution Algorithm Based on Simplex Operator
Liu Jian-xun · Jisuanji gongcheng · 2009
Aiming at the slow convergence of DE/rand/1/bin strategy, this paper presents a hybrid optimization algorithm named SMDE incorporated Simplex Method(SM) into Differential Evolution(DE) algorithm.It takes use of good global searching ability of DE and good local searching ability and fast convergence of SM, so that the convergence speed and solution precision of DE are improved.Experimental results on several classical Benchmarks complex functions show that the hybrid optimization algorithm is effective, efficient and fairly robust to initial conditions, and its performances excels those single optimization methods.