Brain storm optimization with agglomerative hierarchical clustering analysis

Abstract

Brain storm optimization (BSO) is a relatively new swarm intelligence algorithm, which simulates the problem-solving process of human brainstorming. In General, BSO employs flat clustering which has a number of drawbacks. In this paper, the agglomerative hierarchical clustering is introduced into BSO and its impact on the performance of the creating operator is then analyzed. The proposed algorithm is applied to numerical optimization problems in comparison with the BSO with k-means Clustering. Experimental results show that the proposed algorithm achieves satisfactory results and guarantees a high coverage rate.