MATEC Web Conf.
Volume 139, 20172017 3rd International Conference on Mechanical, Electronic and Information Technology Engineering (ICMITE 2017)
|Number of page(s)||5|
|Published online||05 December 2017|
Whale optimization algorithm with nonlinear control parameter
1 College of Information Engineering, Guangxi University of Foreign Language, Nanning 530222, PR China
2 Key Laboratory of Economics System Simulation, Guizhou University of Finance & Economics, Guiyang 550025, PR China
* Corresponding author: email@example.com
Whale optimization algorithm (WOA) is a relatively novel intelligence optimization technique which has been shown to be competitive to other population-based algorithms. However, the control parameter a is a major factor to affect the algorithm’s convergence precision and speed. At present, few of them are aiming at control parameter setting in WOA algorithm. This paper proposes corresponding improved WOA algorithm with different nonlinear adjustment strategy of control parameter a by adopting sinusoid, cosine, tangential, logarithmic and quadratic curves. The experimental results for six benchmark test functions show that the proposed nonlinear adjustment strategies are superior to the classical linear strategy.
Key words: whale optimization algorithm; / control parameter; / nonlinear; / benchmark test function
© The Authors, published by EDP Sciences, 2017
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (http://creativecommons.org/licenses/by/4.0/).
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