A Probabilistic Hybrid Differential Evolution Algorithm
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.
Key wordsGlobal optimization population set β-distribution continuous variable probabilistic adaption
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