ARO: a new model-free optimization algorithm inspired from asexual reproduction

Farasat, A, Menhaj, MB, Mansouri, T ORCID: https://orcid.org/0000-0003-1539-5546 and Moghadam, MRS 2010, 'ARO: a new model-free optimization algorithm inspired from asexual reproduction' , Applied Soft Computing, 10 (4) , pp. 1284-1292.

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Abstract

This paper proposes a new individual based optimization algorithm, which is inspired from asexual reproduction known as a remarkable biological phenomenon, called as Asexual Reproduction Optimization (ARO). ARO can be essentially considered as an evolutionary based algorithm that mathematically models the budding mechanism of asexual reproduction. In ARO, each individual produces an offspring called bud through a reproduction mechanism; thereafter parent and its offspring compete according to a performance index obtained from the underlying objective function of the given optimization problem. This process leads to the fitter individual. ARO's adaptive search ability and its strong and weak points are described in this paper. Furthermore, the ARO convergence to the global optimum is mathematically analyzed. To approve the effectiveness of the ARO performance, it is tested with several benchmark functions frequently used in the area of optimization. Finally, the ARO performance is statistically compared with that of Particle Swarm Optimization (PSO). Results of simulation illustrate that ARO remarkably outperforms PSO.

Item Type: Article
Schools: Schools > School of Computing, Science and Engineering > Salford Innovation Research Centre
Journal or Publication Title: Applied Soft Computing
Publisher: Elsevier
ISSN: 1568-4946
Related URLs:
Depositing User: T Mansouri
Date Deposited: 09 Jun 2021 09:58
Last Modified: 09 Jun 2021 09:58
URI: http://usir.salford.ac.uk/id/eprint/60893

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