Solution clustering analysis in brain storm optimization algorithm

In swarm intelligence algorithms, premature convergence happens partially due to the solutions getting clustered together, and not diverging again. However, solution clustering is not always harmful for optimization. The solution clustering strategy is utilized in brain storm optimization (BSO) to guide individuals to move toward the better and better areas. The information of clusters indicates the solutions´ distribution in the search space, which could be utilized to reveal the landscapes and other proprieties of problems being optimized. In this paper, the solution clustering, and other properties of the brain storm optimization algorithm are analyzed and discussed. Experimental results show that brain storm optimization is a very promising algorithm for solving different kinds of problems.