Abstract
In this paper, a new swarm intelligence algorithm based on orcas behaviors is proposed for problem solving. The algorithm called Orcas Algorithm (OA) consists in simulating the orcas life style and in particular their social organization, their echolocation practice and their hunting techniques. The experimental study we conducted tested the designed algorithm as well as recent state-of-the-art evolutionary algorithms for comparison purposes. The experiments were performed using a public dataset describing mazes with four level of complexity. The overall obtained results clearly show the superiority of OA algorithm over the others. This finding opens the way to other problems to solve to benefit from OA robustness.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Kennedy, J., Eberhart, R.C.: Swarm Intelligence. Morgan Kaufmann Publishers Inc., San Francisco \(\copyright \)(2001). ISBN 1-55860-595-9
Dorigo, M., Stützle, T.: Ant Colony Optimization. MIT Press, Cambridge (2004). ISBN 0-262-04219-3
Drias, H., Sadeg, S., Yahi, S.: Cooperative bees swarm for solving the maximum weighted satisfiability problem. LNCS, pp. 318–325. Springer (2005)
Zambrano-Bigiarini, M., Clerc, M., Rojas, R.: Standard particle swarm optimisation 2011 at CEC-2013: a baseline for future PSO improvements. In: 2013 IEEE Congress on Evolutionary Computation (CEC), pp. 2337–2344. https://doi.org/10.1109/CEC.2013.6557848
Yang, X.S.: A new metaheuristic bat-inspired algorithm. In: Gonzalez, J.R., et al. (eds.) NICSO 2010, vol. 284, pp. 65–74. Springer, Heidelberg (2010)
Yang, X.S., He, X.: Firefly algorithm: recent advances and applications. Int. J. Swarm Intelligence 1(1), 36–50 (2013). https://doi.org/10.1504/IJSI.2013.055801
Wang, G.G., Dos Santos Coelho, L., Gao, X.Z., Deb, S.: A new metaheuristic optimisation algorithm motivated by elephant herding behaviour. Int. J. Bio-Inspired Comput. 8(6), 394 (2016)
Mandal, S.: Elephant swarm water search algorithm for global optimization. Sādhanā 43, 2 (2018). https://doi.org/10.1007/s12046-017-0780-z
Mirjalili, S., Lewis, A.: The whale optimization algorithm. Adv. Eng. Softw. 95, 51–67 (2016)
Orca Social Organization: OrcaLab, 24 February 2019
All About Killer Whales. Communication and Echolocation — SeaWorld Parks and Entertainment. https://seaworld.org/animals/all-about/killer-whale/communication/. Accessed 30 Jan 2019
Killer Whale Hunting Strategies, 24 November 2014. http://www.pbs.org/wnet/nature/killer-whales-killer-weapon-brain/11352/. Accessed 02 Jan 2019
Welcome to Maze Benchmark. Maze Benchmark for Evolutionary Algorithms. https://mazebenchmark.github.io/. Accessed 15 Apr 2019
Bagnall, A.J., Zatuchna, Z.V.: On the classification of maze problems. In: Bull, L., Kovacs, T. (eds.) Foundations of Learning Classifier Systems, vol. 183, pp. 305–316. Springer, Heidelberg (2005)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Drias, H., Drias, Y., Khennak, I. (2020). A New Swarm Algorithm Based on Orcas Intelligence for Solving Maze Problems. In: Rocha, Á., Adeli, H., Reis, L., Costanzo, S., Orovic, I., Moreira, F. (eds) Trends and Innovations in Information Systems and Technologies. WorldCIST 2020. Advances in Intelligent Systems and Computing, vol 1159. Springer, Cham. https://doi.org/10.1007/978-3-030-45688-7_77
Download citation
DOI: https://doi.org/10.1007/978-3-030-45688-7_77
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-45687-0
Online ISBN: 978-3-030-45688-7
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)