A hybrid method for optimization (discrete PSO + CLA)
Behnam Jafarpour, Mohammad Reza Meybodi, Saeed Shiry Ghidary · 2007
PSO is an evolutionary algorithm that is inspired from collective behavior of animals such as fish schooling or bird flocking. One of the drawbacks of this model is premature convergence and trapping in local optima. In this paper we propose a solution to this problem in discrete version of PSO that uses Learning Automata and introduce a cellular learning automata (CLA) based discrete PSO. Experimental results on five optimization problems show the superiority of the proposed algorithm.