A greedy cluster-based tribes optimization algorithm

In this paper, we propose a cluster-based optimization algorithm. It is a greedy agent-based tribal particle swarm optimization algorithm (GATPSO) which adapts the tribes by removing/generating particles and reconstructing tribal links in order to encourage better tribes to proliferate, and causes reducing the computation cost and preventing local optimal solutions. The proposed approach is applied to several numeric benchmarks. Results of this study demonstrate the effectiveness of the proposed algorithm.