Summary
In this chapter we propose a hybrid point generation scheme in the differential evolution (DE) algorithm. In particular, we propose a DE algorithm that uses a probabilistic combination of the point generation by the β-distribution and the point generation by mutation. Numerical results suggest that the resulting algorithm is superior to the original version both in terms of the number of function evaluations and cpu times.
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© 2007 Springer Science+Business Media, LLC
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Ali, M.M. (2007). A Probabilistic Hybrid Differential Evolution Algorithm. In: Törn, A., Žilinskas, J. (eds) Models and Algorithms for Global Optimization. Optimization and Its Applications, vol 4. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-36721-7_11
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DOI: https://doi.org/10.1007/978-0-387-36721-7_11
Publisher Name: Springer, Boston, MA
Print ISBN: 978-0-387-36720-0
Online ISBN: 978-0-387-36721-7
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