Markov Model and Convergence Analysis Based on Cuckoo Search Algorithm
Yang Song-ming · Jisuanji gongcheng · 2012
In order to perfect the convergence theory of Cuckoo Search(CS) algorithm,the Markov chain model of the CS algorithm is established and the property of the limited and homogeneous of Markov chain is analyzed.On the basis of this,through the analysis of the state transition process of a group of nest position,the stochastic sequence enters to the optimal state set.And CS algorithm meets the global convergence qualification of random search algorithms.Simulation experimental results show that CS algorithm achieves the global optimization,and the global convergence is ensured.