Volume 16, Issue 3 (JIAEEE Vol.16 No.3 2019)                   Journal of Iranian Association of Electrical and Electronics Engineers 2019, 16(3): 147-155 | Back to browse issues page

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Kalantari M, Sohrabi S, Rashidy Kanan H. A Hybrid Optimization Algorithm Based on Genetic Algorithm and Hyper Spherical Search Based on Chaos Theory. Journal of Iranian Association of Electrical and Electronics Engineers 2019; 16 (3) :147-155
URL: http://jiaeee.com/article-1-376-en.html
A Hybrid Optimization Algorithm Based on Genetic Algorithm and Hyper Spherical Search Based on Chaos Theory
Mohammad Kalantari * , Sakineh Sohrabi , Hamidreza Rashidy Kanan
Shahid Rajaee Teacher Training University
Abstract:   (3891 Views)
A hybrid optimization algorithm based on genetic algorithm and choatic hyper spherical search method is proposed. In the proposed method, in order to increase the efficiency of searching the optimal solution, chaos theory along with  genetic operators have been used. This, not only makes the results of the proposed algorithm definite and decreases their standard deviation, but also resolves the weakness of the hyper spherical search optimization algorithm based on chaos theory including the speed of convergence and the weak performance in some benchmark functions. The simulation results on the standard benchmark functions show that the proposed algorithm not only has faster convergence, but also acts as a more accurate search algorithm to find the optimal solution in comparison to the standard hyper spherical search algorithm, chaotic hyper sherical search algorithm, and some other optimization algorithms such as genetic, particle swarm, and harmony search algorithm.

Keywords: Metaheuristic Algorithm based on Chaos Theory, Hyper Sphere Search Algorithm, Genetic Algorithm, Chaos Theory
Full-Text [PDF 768 kb]   (1267 Downloads)    
Type of Article: Research | Subject: Power
Received: 2017/08/19 | Accepted: 2018/08/4 | Published: 2019/09/4
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