Talk by Dirk Arnold, Dalhousie University, CA
We consider the problem of devising an approach for handling inequality constraints in evolution strategies that allows converging linearly to optimal solutions on sphere functions with a single linear constraint. An analysis of the single-step behaviour of the (1+1)-ES shows that the task of balancing improvements in the objective with those in the constraint function is quite delicate, and that adaptive approaches need to be carefully designed in order to avoid failure. Based on the understanding gained, we propose a simple augmented Lagrangian approach and experimentally demonstrate good performance on a broad range of sphere functions as well as on moderately ill-conditioned ellipsoids with a single linear constraint.
My research interests are in evolutionary computation, optimization, image processing, and computer graphics and animation. A complete listing of publications can be found here or on my Google scholar page. Recent papers include:
X. Gao, S. Brooks, and D. V. Arnold
Automated parameter tuning for tone mapping using visual saliency
Computers & Graphics, to appear, 2015.
M. Hellwig and D. V. Arnold
Comparison of constraint handling mechanisms for the (1,λ)-ES on a simple constrained problem
Evolutionary Computation, to appear, 2015.