Abstract
In this paper, performance of basic Artificial Bee Colony, Bees and Differential evolution algorithms is compared on eight well-known benchmark problems. Most of experimental results show that the DE/best/1/exp scheme has the best performance on unimodal problems, Bees algorithm has the second performance except Quadric and Rosenbrock functions. On multimodal problems Bees algorithm has the best performance, and Artificial Bee Colony is the second.
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References
Kun-qi, L., Li-shan, K., Zhi-zhuo, Z.: Brief Report of Research on Cognizing the Subarea of Evolutionary Computation. Computer Science (I)Â 36(7) (2009)
Kun-qi, L., Li-shan, K., Zhi-zhuo, Z.: Brief Report of Research on Cognizing the Subarea of Evolutionary Computation. Computer Science (II)Â 36(8) (2009)
Zong-ben, X.: Computational Intelligence - simulated Evolutionary Computation, vol. I. Higher Education Press, Beijing (2004)
Ran, H., Yong-ji, W., Qing, W.: An Improved Particle Swarm Optimization Based on Self-Adaptive Escape Velocity. Journal of Software 16(12) (2005)
Basturk, B., Karaboga, D.: An artificial bee colony (abc) algorithm for numeric function optimization. In: IEEE Swarm Intelligence Symposium 2006,Indianapolis, Indiana, USA (May 2006)
Karaboga, D., Basturk, B.: A powerful and efficient algorithm for numerical function optimization:Artificial bee colony (abc) algorithm. Journal of Global Optimization 39(3), 459–471 (2007)
Pham, D.T., Ghanbarzadeh, A., Koc, E., Otri, S., Rahim, S., Zaidi, M.: The Bees Algorithm. Technical Note,Manufacturing Engineering Centre,Cardiff University,UK (2005)
Pham, D.T., Ghanbarzadeh, A., Koc, E., Otri, S., Rahim, S., Zaidi, M.: The Bees Algorithm,A Novel Tool for Complex Optimisation Problems. In: Proc. 2nd Virtual International Conference on Intelligent Production Machines and Systems, pp. 454–459. Elsevier, Oxford (2006)
Storn, R., Price, K.: Differential evolution: A simple and efficient heuristic for global optimization over continuous spaces [J]. Journal of Global Optimization 11, 341–359 (1997)
Storn, R., Price, K.: Differential evolution ——A simple and efficient adaptive scheme for global optimization over continuous spaces. Technical Report TR - 95 - 012. International Computer Science Institute, Berkely, California (1995)
Liang, X., Guang-ming, D., Quan-yuan, Z.: Overview of differential evolution algorithm and its improved algorithms. Computer Engineering and Design 29(1) (2008)
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Li, H., Liu, K., Li, X. (2010). A Comparative Study of Artificial Bee Colony, Bees Algorithms and Differential Evolution on Numerical Benchmark Problems. In: Cai, Z., Tong, H., Kang, Z., Liu, Y. (eds) Computational Intelligence and Intelligent Systems. ISICA 2010. Communications in Computer and Information Science, vol 107. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16388-3_22
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DOI: https://doi.org/10.1007/978-3-642-16388-3_22
Publisher Name: Springer, Berlin, Heidelberg
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