Convergence of artificial plant optimisation algorithm. (1st January 2014) - Fang, Juanyan; Wei, Changcheng
Artificial plant optimisation algorithm is one evolutionary algorithm inspired by the plant growing process, such as photosynthesis, phototropism and apical dominance phenomena. Up to now, it has been applied to many engineering problems successfully. However, the global convergence analysis is not reported yet. In this paper, we provide the global convergence for the standard version with Markov chain. The theoretical analysis shows that the artificial plant optimisation algorithm is convergent to global optimum with probability one.