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HAIS
2009
Springer

Hybrid Evolutionary Algorithm for Solving Global Optimization Problems

11 years 6 months ago
Hybrid Evolutionary Algorithm for Solving Global Optimization Problems
Differential Evolution (DE) is a novel evolutionary approach capable of handling non-differentiable, non-linear and multi-modal objective functions. DE has been consistently ranked as one of the best search algorithm for solving global optimization problems in several case studies. This paper presents a simple and modified hybridized Differential Evolution algorithm for solving global optimization problems. The proposed algorithm is a hybrid of Differential Evolution (DE) and Evolutionary Programming (EP). Based on the generation of initial population, three versions are proposed. Besides using the uniform distribution (U-MDE), the Gaussian distribution (G-MDE) and Sobol sequence (S-MDE) are also used for generating the initial population. Empirical results show that the proposed versions are quite competent for solving the considered test functions.
Radha Thangaraj, Millie Pant, Ajith Abraham, Youak
Added 25 Jul 2010
Updated 25 Jul 2010
Type Conference
Year 2009
Where HAIS
Authors Radha Thangaraj, Millie Pant, Ajith Abraham, Youakim Badr
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