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A numerical study of some modified differential evolution algorithms. (English) Zbl 1079.90106

Summary: Modifications in mutation and localization in acceptance rule are suggested to the differential evolution algorithm for global optimization. Numerical experiments indicate that the resulting algorithms are considerably better than the original differential evolution algorithm. Therefore, they offer a reasonable alternative to many currently available stochastic algorithms, especially for problems requiring ’direct search type’ methods. Numerical study is carried out using a set of 50 test problems many of which are inspired by practical applications.

MSC:

90C26 Nonconvex programming, global optimization

Software:

INTOPT_90; WEDGE; Genocop
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References:

[1] Storn, R.; Price, K., Differential evolution—A simple and efficient heuristic for global optimization over continuous spaces, Journal of global optimization, 11, 341-359, (1997) · Zbl 0888.90135
[2] Ali, M.M.; Törn, A., Population set based global optimization algorithms: some modifications and numerical studies, Computers and operations research, 31, 10, 1703-1725, (2004) · Zbl 1073.90576
[3] P. Kaelo, Some population set based methods for unconstrained global optimization, PhD thesis, in preparation. · Zbl 1353.90086
[4] Price, K., An introduction to differential evolution, (), 79-108
[5] D. Zaharie, Critical values for the control parameters of differential evolution algorithms, in: R. Matousek, P. Osmera (Eds.), Proceedings of MENDEL 2002, 8th International Mendel Conference on Soft Computing, Bruno, Czech Republic, Bruno University of Technology, Faculty of Mechanical Engineering, Bruno, Czech Republic, 2002, pp. 62-67.
[6] Ali, M.M.; Törn, A., Topographical differential evolution using pre-calculated differentials, (), 1-17 · Zbl 1211.90175
[7] M.M. Ali, C. Khompatraporn, Z.B. Zabinsky, A numerical evaluation of several stochastic algorithms on selected continuous global optimization test problems, Journal of Global Optimization, in press. · Zbl 1093.90028
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