Novel Oppositional Hybrid Differential Evolution Algorithm Based on Swarm Intelligence
Xing Xu · Journal of Chinese Computer Systems · 2009
A novel oppositional hybrid differential evolution(DE)algorithm,which combined with particle swarm intelligence(PSO)thinking,is presented.In terms of the superior performance on function optimization for DE and PSO,This paper detects the underlying relationship between them.In the new algorithm(ODE-SI),the experiential memory ideas of PSO are not only retained,but the opposition-based learning is also applied.It is conducive to high convergence and good population diversity.Some experiments are used to compare the ODE-SI with other DE and PSO algorithms.The results from our study show that ODE-SI keeps the most rapid convergence rate of all techniques and obtains the global optima for most benchmark problems.