Using the Conjugate Gradient & Parallel Tangent to Improve the Ant Lion Algorithm


Authors : Radhwan Basim Thanoon, Zyiad Adrees Hamad

Volume/Issue : Volume 5 - 2020, Issue 5 - May

Google Scholar : http://bitly.ws/9nMw

Scribd : https://bit.ly/2M8377t

Abstract : In this paper, A hybrid algorithm is proposed, the( ALO) Ant lion algorithm, Along with classical algorithms. The hybrid algorithm optimizes the randomly generated primary community, dependent on a Conjugate Gradient algorithm (CG) and once with a Parallel Shadow algorithm (Partan). The test was applied to (15) high-performance optimization functions of different dimensions and different frequencies.

Keywords : Ant lion Optimization, meta-Heuristic algorithms, Conjugate Gradient methods, Parallel Tangent method, unconstrained Optimization

In this paper, A hybrid algorithm is proposed, the( ALO) Ant lion algorithm, Along with classical algorithms. The hybrid algorithm optimizes the randomly generated primary community, dependent on a Conjugate Gradient algorithm (CG) and once with a Parallel Shadow algorithm (Partan). The test was applied to (15) high-performance optimization functions of different dimensions and different frequencies.

Keywords : Ant lion Optimization, meta-Heuristic algorithms, Conjugate Gradient methods, Parallel Tangent method, unconstrained Optimization

Video Explanation for Published paper

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