Global-Best Brain Storm Optimization Algorithm Based on Discussion Mechanism and Difference Step

Abstract

Global-best brain storm optimization algorithm based on discussion mechanism and difference step (DDGBSO) is proposed in this paper to solve the problems that the traditional brain storm optimization algorithm has low convergence speed and poor optimization accuracy. The difference step is applied to replace the original mutation strategy, which improves the convergence speed by increasing the search space in the early iteration stage. The following global optimal strategy and discussion mechanism are innovatively combined to take full advantage of the global optimal information and to optimize the procedure of the BSO algorithm. Based on the CEC2013 benchmark test suit, 15 classical test functions are selected and multiple sets of simulations are conducted by Matlab. The simulation results show that DDGBSO has better performance than BSO and other improved BSO algorithms and improves the convergence speed and the optimization accuracy.