06068758

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06068758 Zhabitskaya, Evgeniya Constraints on control parameters of asynchronous differential evolution. Adam, Gheorghe (ed.) et al., Mathematical modeling and computational science. International conference, MMCP 2011, Star\'a Lesn\'a, Slovakia, July 4--8, 2011. Revised selected papers. Berlin: Springer (ISBN 978-3-642-28211-9/pbk). Lecture Notes in Computer Science 7125, 322-327 (2012). 2012 Berlin: Springer EN global optimization derivative-free optimization premature convergence control parameters evolution strategy

doi:10.1007/978-3-642-28212-6_40

Summary: The efficiency of an algorithm to find the global minimum depends on its ability to keep population diversity during evolutionary iterations. Statistical variance can serve as a measure of population diversity. We analyse the expected population variance after mutation and crossover for best/1/bin strategy of Classical Differential Evolution and for new strategies of a novel Asynchronous Differential Evolution. Relations between the control parameters ($N _{p }, F, C _{r })$ of algorithms and the extension factor of population variance are derived. Constraints on control parameters to prevent premature convergence of the algorithm are suggested and compared with phase portraits (convergence domains) for several benchmark functions.