Abstract
JDE, proposed by J. Brest and et al. is an efficient variant of differential evolution algorithm. JDE algorithm is focused on global search ability. However, its local search ability also need further improvement. Therefore a novel variant of JDE is proposed, which combines JDE and a local search operator simplex crossover operator aiming to improve the local search ability of JDE. The experimental results show that the novel hybrid algorithm improves the performance of JDE in term of precision and efficiency.
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References
Storn, R., Price, K.V., Lampinen, J.: Differential Evolution - A Practical Approach to Global Optimization. Springer, Berlin (2005)
Lampinen, J., Zelinka, I.: On stagnation of the differential evolution algorithm. In: Ošmera, P. (ed.) Proc. of MENDEL 2000, 6th International Mendel Conference on Soft Computing, Brno, Czech Republic, June 7-9, pp. 76–83 (2000)
Brest, J., Greiner, S., Bošković, B., Mernik, M., Žumer, V.: Self-adapting Control parameters in differential evolution: a comparative study on numerical benchmark problems. IEEE Transactions on Evolutionary Computation 10(6), 646–657 (2006)
Gamperle, R., Muller, S.D., Koumoutsakos, A.: Parameter study for differential evolution. In: WSEAS NNA-FSFS-EC 2002, Interlaken, Switzerland, February 11-15 (2002)
Zaharie, D.: Control of population diversity and adaptation in differential evolution algorithms. In: Matousek, D., Osmera, P. (eds.) Proc. of MENDEL 2003, 9th International Conference on Soft Computing, Brno, Czech Republic, pp. 41–46 (June 2003)
Storn, R., Price, K.: Differential evolution—A simple and efficient heuristic for global optimization over continuous spaces. J. Global Optimiz. 11, 341–359 (1997)
Storn, R., Price, K.: Differential Evolution—A Simple and efficient adaptive scheme for global optimization over continuous spaces, Berkeley, CA, Tech. Rep. TR-95-012 (1995), citeseer.ist.psu.edu/article/storn95differential.html
Yong, W., Zi Xing, C., Guan Qi, G., Yu Ren, Z.: Multi-objective optimization and hybrid evolutionary algorithm to solve constrained optimization problems. IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics 37(3), 560–575 (2007)
Xin, Y., Liu, Y., Lin, G.: Evolutionary Programming Made Faster. IEEE Transaction on Evolutionary Computation 3, 82–102 (1999)
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Liu, X., Shi, L., Chen, R. (2011). JDEL: Differential Evolution with Local Search Mechanism for High-Dimensional Optimization Problems. In: Qi, L. (eds) Information and Automation. ISIA 2010. Communications in Computer and Information Science, vol 86. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19853-3_50
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DOI: https://doi.org/10.1007/978-3-642-19853-3_50
Publisher Name: Springer, Berlin, Heidelberg
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