Asynchronous differential evolution

Authors:
Evgeniya Zhabitskaya;Mikhail Zhabitsky
Affiliations:
University Dubna, Dubna, Russia;Joint Institute for Nuclear Research, Dubna, Russia
Venue:
MMCP'11 Proceedings of the 2011 international conference on Mathematical Modeling and Computational Science
Year:
2011

Citing 3
Cited 2

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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 with adaptive correlation matrix

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Abstract

Differential Evolution (DE) is an algorithm to solve possibly nonlinear and non-differentiable global optimization problems. Classical Differential Evolution (CDE) employs a synchronous generation-based evolution strategy. We propose a modification of the CDE algorithm by incorporating mutation, crossover and selection operations into an asynchronous strategy. A novel Asynchronous Differential Evolution (ADE) is well suited for parallel optimization. Moreover even in the sequential mode its rate of convergence is competitive to CDE. The performance of the Asynchronous Differential Evolution is reported on a set of benchmark functions.