TY - CONF T1 - Evolving cognitive and social experience in Particle Swarm Optimization through Differential Evolution T2 - IEEE Congress on Evolutionary Computation, 2010. CEC 2010. (IEEE World Congress on Computational Intelligence) Y1 - 2010 A1 - M. G. Epitropakis A1 - V. P. Plagianakos A1 - M. N. Vrahatis KW - cognitive experience KW - convergence KW - differential evolution KW - evolutionary computation KW - particle swarm optimisation KW - particle swarm optimization KW - social experience AB - In recent years, the Particle Swarm Optimization has rapidly gained increasing popularity and many variants and hybrid approaches have been proposed to improve it. Motivated by the behavior and the proximity characteristics of the social and cognitive experience of each particle in the swarm, we develop a hybrid approach that combines the Particle Swarm Optimization and the Differential Evolution algorithm. Particle Swarm Optimization has the tendency to distribute the best personal positions of the swarm near to the vicinity of problem’s optima. In an attempt to efficiently guide the evolution and enhance the convergence, we evolve the personal experience of the swarm with the Differential Evolution algorithm. Extensive experimental results on twelve high dimensional multimodal benchmark functions indicate that the hybrid variants are very promising and improve the original algorithm. JF - IEEE Congress on Evolutionary Computation, 2010. CEC 2010. (IEEE World Congress on Computational Intelligence) CY - Barcelona, Spain ER -