Journal of Global Optimization
Differential Evolution: A Practical Approach to Global Optimization (Natural Computing Series)
Differential Evolution: A Practical Approach to Global Optimization (Natural Computing Series)
Differential evolution algorithm with strategy adaptation for global numerical optimization
IEEE Transactions on Evolutionary Computation
JADE: adaptive differential evolution with optional external archive
IEEE Transactions on Evolutionary Computation
Constraints on control parameters of asynchronous differential evolution
MMCP'11 Proceedings of the 2011 international conference on Mathematical Modeling and Computational Science
Asynchronous differential evolution
MMCP'11 Proceedings of the 2011 international conference on Mathematical Modeling and Computational Science
IEEE Transactions on Evolutionary Computation
Differential Evolution: A Survey of the State-of-the-Art
IEEE Transactions on Evolutionary Computation
JADE, an adaptive differential evolution algorithm, benchmarked on the BBOB noiseless testbed
Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
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Differential evolution (DE) is an efficient algorithm to solve global optimization problems. It has a simple internal structure and uses a few control parameters. In this paper we incorporate crossover based on adaptive correlation matrix into Asynchronous differential evolution (ADE). Thanks to the proposed crossover the novel algorithm automatically adapts to the landscape of the optimized objective function. Combined with an adaptive scheme for the mutation scale factor and an automatic inflation of the population size this results in quasi parameter-free algorithm from the user's point of view. The performance of the Asynchronous differential evolution with adaptive correlation matrix is reported on the set of BBOB-2012 benchmark functions.