Journal of Global Optimization
Influence of crossover on the behavior of Differential Evolution Algorithms
Applied Soft Computing
A simulated annealing driven multi-start algorithm for bound constrained global optimization
Journal of Computational and Applied Mathematics
Recent advances in differential evolution: a survey and experimental analysis
Artificial Intelligence Review
Differential evolution with generalized differentials
Journal of Computational and Applied Mathematics
Journal of Global Optimization
Differential evolution for dynamic environments with unknown numbers of optima
Journal of Global Optimization
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In this paper we derive the probability distribution of trial points in the differential evolution (de) algorithm, in particular the probability distribution of points generated by mutation. We propose a point generation scheme that uses an approximation to this distribution. The scheme can dispense with the differential vector used in the mutation of de. We propose a de algorithm that replaces the differential based mutation scheme with a probability distribution based point generation scheme. We also propose a de algorithm that uses a probabilistic combination of the point generation by the probability distribution and the point generation by mutation. A numerical study is carried out using a set of 50 test problems, many of which are inspired by practical applications. Numerical results suggest that the new algorithms are superior to the original version both in terms of the number of function evaluations and cpu times.