Mixed mutation strategy embedded differential evolution
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
A Differential Evolution Based Time-Frequency Atom Decomposition for Analyzing Emitter signals
MDAI '09 Proceedings of the 6th International Conference on Modeling Decisions for Artificial Intelligence
Interpolated differential evolution for global optimisation problems
International Journal of Computing Science and Mathematics
The modified differential evolution algorithm (MDEA)
ACIIDS'12 Proceedings of the 4th Asian conference on Intelligent Information and Database Systems - Volume Part III
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Differential Evolution (DE) has emerged as a powerful tool for solving optimization problems in the last few years. However, the convergence rate of DE still does not meet all the requirements, and attempts to speed up differential evolution are considered necessary. In order to improve the performance of DE, we propose a modified DE algorithm called DEPCX which uses parent centric approach to manipulate the solution vectors. The performance of DEPCX is evaluated on a test bed of five functions. Numerical results are compared with original differential evolution (DE) and with TDE, another recently modified version of DE. Empirical results indicate that this modification enables the algorithm to get a better transaction between the convergencerate and robustness.