Cuckoo search algorithm with dynamic inertia weight
Zhou Hua · Caai Transactions on Intelligent Systems · 2015
In order to improve the search ability and optimization accuracy of cuckoo search algorithm,the cuckoo search with dynamic inertia weight is proposed. By utilizing the dynamic inertia weight,the improved cuckoo search updates the next nest position based on the former best nest position that has been saved with dynamic inertia weight,which can well balance the relation between population exploration and development capabilities. This paper also has a convergence analysis of the improved cuckoo search by the characteristic equation. The performance of the new method is compared with the basic cuckoo search,particle swarm optimization,ant colony optimization and other algorithms,showing that the improved cuckoo search algorithm can significantly reduce the number of iterations and running time,and can effectively improve the convergence speed and convergence precision.