Abstract
Differential evolution algorithm is a simple stochastic global optimization algorithm.In this paper, the idea of simulated annealing is involved into original differential evolution algorithm and a simulated annealing-based differential evolution algorithm is proposed. It is almost as simple for implement as differential evolution algorithm, but it can improve the abilities of seeking the global excellent result and evolution speed. The experiment results demonstrate that the proposed algorithm is superior to original differential evolution algorithm.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Stron, R., Price, K.: Differential evolution-a simple and efficient adapative scheme for global optimization over continuous spaces.Technical Report TR-95-012,ICSI (1995)
Babu, B.V., Jehan, M.M.L.: Differential evolution for multiobjective optimization [J]. Evolutionary Computation 4, 8–12 (2003)
GaoFei: Differential evolution algorithms with extinction based on space contraction[J]. Complex systems and complexity science 19(1), 49–52 (2004)
Guangming, L.: Differential evolution algorithms and modification[J]. Systems Engineering 23(2), 108–111 (2005)
Wang, F.S., Jang, H.J.: Parameter estimation of a bioreaction model by hybrid differential evolution [J]. Evolutionary Computation 1, 16–19 (2000)
Fan, H., Lampinen, J.: A trigonometric mutation operation to differential evolution [J]. Journal of Global Optimization 27, 105–129 (2003)
Thomsen, R.: Multimodaloptimization using crowding-based differential evolution. In: Proceedings of the 2004 Congress on Evolutionary Computation, vol. 2, pp. 1382–1389 (1389)
Hrstka, O., Kucerova, A.: Improvements of real coded genetic algorithms based on differential operators preventing premature convergence[J]. Engineering Software 35, 237–246 (2004)
Lampinen, J.: A constraint handling approach for the differential evolution algorithm [J]. Evolutionary Computation 2, 12–17 (2002)
lishan, K.: Non-numeric parallel algorithm (first volume) – Simulated annealing algorithm [M]. Science Publisher, Beijing (1997)
Xuemei, W., Yihe, W.: The combination of Simulated annealing algorithm and genetic algorithm[J]. Chinese Journal of Computers 20(4), 381–384 (1997)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Liu, K., Du, X., Kang, L. (2007). Differential Evolution Algorithm Based on Simulated Annealing. In: Kang, L., Liu, Y., Zeng, S. (eds) Advances in Computation and Intelligence. ISICA 2007. Lecture Notes in Computer Science, vol 4683. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74581-5_13
Download citation
DOI: https://doi.org/10.1007/978-3-540-74581-5_13
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74580-8
Online ISBN: 978-3-540-74581-5
eBook Packages: Computer ScienceComputer Science (R0)