no code implementations • 23 Jan 2019 • Patrick Spettel, Hans-Georg Beyer
Based on that, expressions for the steady state of the mean value iterative system are derived.
no code implementations • 15 Dec 2018 • Patrick Spettel, Hans-Georg Beyer
Approximate deterministic evolution equations are formulated for analyzing the strategy's dynamics.
1 code implementation • 26 Jul 2018 • Michael Hellwig, Hans-Georg Beyer
The development, assessment, and comparison of randomized search algorithms heavily rely on benchmarking.
no code implementations • 15 Jun 2018 • Patrick Spettel, Hans-Georg Beyer, Michael Hellwig
This paper addresses the development of a covariance matrix self-adaptation evolution strategy (CMSA-ES) for solving optimization problems with linear constraints.
no code implementations • 12 Jun 2018 • Michael Hellwig, Hans-Georg Beyer
Benchmarking plays an important role in the development of novel search algorithms as well as for the assessment and comparison of contemporary algorithmic ideas.
2 code implementations • 18 May 2017 • Ilya Loshchilov, Tobias Glasmachers, Hans-Georg Beyer
The Covariance Matrix Adaptation Evolution Strategy (CMA-ES) is a popular method to deal with nonconvex and/or stochastic optimization problems when the gradient information is not available.