Abstract
The β -distribution is used as a point generation scheme in global optimization. Two population set-based global optimization algorithms are considered. These are the differential evolution (DE) and the controlled random search (CRS) algorithms. The point generation schemes of DE and CRS are hybridized with the β random variate. The hybridization uses a probabilistic combination of the point generation by the β -distribution and the point generation by DE or CRS. Numerical experiments are carried out using both test and practical problems. Numerical results suggest that the resulting algorithms are superior to their respective original counterpart.
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