Convergence of artificial plant optimisation algorithm
Juanyan Fang, Changcheng Wei · International Journal of Computing Science and Mathematics · 2014
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.