Title: Convergence of artificial plant optimisation algorithm

Authors: Juanyan Fang; Changcheng Wei

Addresses: Department of Mathematics and Computer Science, Tongling University, Tongling, Anhui, China ' Department of Human Resources, Tongling University, Tongling, Anhui, China

Abstract: 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.

Keywords: artificial plant optimisation algorithm; APOA; phototropism; global convergence; photosynthesis; Markov chain; evolutionary algorithms.

DOI: 10.1504/IJCSM.2014.064069

International Journal of Computing Science and Mathematics, 2014 Vol.5 No.2, pp.174 - 183

Received: 04 Oct 2013
Accepted: 22 Feb 2014

Published online: 20 Sep 2014 *

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