TY - GEN
T1 - Chaotic elephant herding optimization algorithm
AU - Tuba, Eva
AU - Capor-Hrosik, Romana
AU - Alihodzic, Adis
AU - Jovanovic, Raka
AU - Tuba, Milan
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/3/23
Y1 - 2018/3/23
N2 - Swarm intelligence algorithms represent stochastic optimization algorithms that proved to be powerful for finding suboptimal solutions for hard optimization problems. Elephant herding optimization algorithm is a rather new and promising representative of that class of optimization algorithms that has already been used in numerous applications. In recent years, chaotic maps were incorporated into the swarm intelligence algorithms in order to improve the search quality. In this paper we introduced two different chaotic maps into the original elephant herding optimization algorithm. The proposed methods were tested on 15 benchmark functions from CEC 2013. Obtained results were compared to the regular elephant herding optimization algorithm as well to the particle swarm optimization. Test results proved that the proposed chaotic elephant herding optimization algorithm has better performance and obtained better results.
AB - Swarm intelligence algorithms represent stochastic optimization algorithms that proved to be powerful for finding suboptimal solutions for hard optimization problems. Elephant herding optimization algorithm is a rather new and promising representative of that class of optimization algorithms that has already been used in numerous applications. In recent years, chaotic maps were incorporated into the swarm intelligence algorithms in order to improve the search quality. In this paper we introduced two different chaotic maps into the original elephant herding optimization algorithm. The proposed methods were tested on 15 benchmark functions from CEC 2013. Obtained results were compared to the regular elephant herding optimization algorithm as well to the particle swarm optimization. Test results proved that the proposed chaotic elephant herding optimization algorithm has better performance and obtained better results.
UR - http://www.scopus.com/inward/record.url?scp=85049107963&partnerID=8YFLogxK
U2 - 10.1109/SAMI.2018.8324842
DO - 10.1109/SAMI.2018.8324842
M3 - Conference contribution
AN - SCOPUS:85049107963
T3 - SAMI 2018 - IEEE 16th World Symposium on Applied Machine Intelligence and Informatics Dedicated to the Memory of Pioneer of Robotics Antal (Tony) K. Bejczy, Proceedings
SP - 213
EP - 216
BT - SAMI 2018 - IEEE 16th World Symposium on Applied Machine Intelligence and Informatics Dedicated to the Memory of Pioneer of Robotics Antal (Tony) K. Bejczy, Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 16th World Symposium on Applied Machine Intelligence and Informatics Dedicated to the Memory of Pioneer of Robotics Antal (Tony) K. Bejczy, SAMI 2018
Y2 - 7 February 2018 through 10 February 2018
ER -