Cover
Vol. 14 No. 2 (2018)

Published: December 31, 2018

Pages: 139-154

Original Article

Analysis of Scalability and Sensitivity for Chaotic Sine Cosine Algorithms

Dunia S. Tahir 1 Ramzy S. Ali
1Electrical Engineering Department University of Basrah Basrah, Iraq
History
  • Received: October 31, 2018
  • Available Online: December 31, 2018
DOI

https://doi.org/10.37917/ijeee.14.2.6

Abstract

Chaotic Sine-Cosine Algorithms (CSCAs) are new metaheuristic optimization algorithms. However, Chaotic Sine-Cosine Algorithm (CSCAs) are able to manipulate the problems in the standard Sine-Cosine Algorithm (SCA) like, slow convergence rate and falling into local solutions. This manipulation is done by changing the random parameters in the standard Sine-Cosine Algorithm (SCA) with the chaotic sequences. To verify the ability of the Chaotic Sine-Cosine Algorithms (CSCAs) for solving problems with large scale problems. The behaviors of the Chaotic Sine-Cosine Algorithms (CSCAs) were studied under different dimensions 10, 30, 100, and 200. The results show the high quality solutions and the superiority of all Chaotic Sine-Cosine Algorithms (CSCAs) on the standard SCA algorithm for all selecting dimensions. Additionally, different initial values of the chaotic maps are used to study the sensitivity of Chaotic Sine-Cosine Algorithms (CSCAs). The sensitivity test reveals that the initial value 0.7 is the best option for all Chaotic Sine-Cosine Algorithms (CSCAs).

Keywords

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