Abstract
A novel hybrid swarm intelligent algorithm DEABC, integrating differential evolution (DE) and artificial bee colony (ABC) algorithm, is proposed in this paper. By using global information obtained form DE population and bee colony, the exploration and exploitation abilities of DEABC algorithm are balanced. The DE population uses the global best to generate offspring every generation. The bee colony acquires the best individual after few generations. The experiments are performed on six benchmark functions to compare the efficiencies of DE, ABC, PSO and DEABC. The numerical results indicate the proposed algorithm outperforms other algorithms in terms of accuracy and convergence speed.
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References
Karaboga, D.: An Idea Based on Honey Bee Swarm for Numerical Optimization. Technical Report TR06 (2005)
Karaboga, D., Ozturk, C.: A Novel Clustering Approach: Artificial Bee Colony (ABC) Algorithm. Applied Soft Computing 11, 652–657 (2011)
Karaboga, D., Basturk, B.: Artificial Bee Colony (ABC) Optimization Algorithm for Solving Constrained Optimization Problems. In: Melin, P., Castillo, O., Aguilar, L.T., Kacprzyk, J., Pedrycz, W. (eds.) IFSA 2007. LNCS (LNAI), vol. 4529, pp. 789–798. Springer, Heidelberg (2007)
Zhao, H.Y., Pei, Z.L., Jiang, J.Q., Guan, R.C., Wang, C.Y., Shi, X.H.: A Hybrid Swarm Intelligent Method Based on Genetic Algorithm and Artificial Bee Colony. In: Tan, Y., Shi, Y., Tan, K.C. (eds.) ICSI 2010. LNCS, vol. 6145, pp. 558–565. Springer, Heidelberg (2010)
Shi, X.H., Li, Y.W., Li, H.J., Guan, R.C., Wang, L.P., Liang, Y.C.: An Integrated Algorithm Based on Artificial Bee Colony Optimization and Particle Swam Optimization. In: 2010 Sixth International Conference on Natural Computation (ICNC), pp. 2586–2590. IEEE Press, Yantai (2010)
Akay, B., Karaboga, D.: A Modified Artificial Bee Colony Algorithm for Real-Parameter Optimization. Information Sciences, 1–23 (2010)
Price, K.V.: An Introduction to Differential Evolution. In: Corne, D., Dorigo, M., Glover, F., Dasgupta, D., Moscato, P., Poli, R., Price, K.V. (eds.) New Ideas in Optimization, pp. 79–108. McGraw-Hill Ltd., London (1999)
Storn, R.: On the Usage of Differential Evolution for Function Optimization. In: Biennial Conference of the North American on Fuzzy Information Processing Society, pp. 519–523. IEEE Press, Berkeley (1996)
Niu, B., Zhu, Y.L., He, X.X.: MCPSO: A Multi-Swarm Cooperative Particle Swarm Optimizer. Applied Mathematics and Computation 185, 1050–1062 (2007)
Karaboga, D., Akay, B.: A Comparative Study of Artificial Bee Colony Algorithm. Applied Mathematics and Computation 214, 108–132 (2009)
Shi, Y.H., Eberhart, R.: A Modified Particle Swarm Optimizer. In: The 1998 IEEE International Conference on Evolutionary Computation Proceedings, pp. 69–73. IEEE Press, Anchorage (1998)
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Li, L., Yao, F., Tan, L., Niu, B., Xu, J. (2012). A Novel DE-ABC-Based Hybrid Algorithm for Global Optimization. In: Huang, DS., Gan, Y., Premaratne, P., Han, K. (eds) Bio-Inspired Computing and Applications. ICIC 2011. Lecture Notes in Computer Science(), vol 6840. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24553-4_74
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DOI: https://doi.org/10.1007/978-3-642-24553-4_74
Publisher Name: Springer, Berlin, Heidelberg
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