Creating Robust Solutions by Means of Evolutionary Algorithms
PPSN V Proceedings of the 5th International Conference on Parallel Problem Solving from Nature
Advances in evolutionary computing
Completely Derandomized Self-Adaptation in Evolution Strategies
Evolutionary Computation
Genetic algorithms with a robust solution searching scheme
IEEE Transactions on Evolutionary Computation
Robust design of multilayer optical coatings by means ofevolutionary algorithms
IEEE Transactions on Evolutionary Computation
Max-min surrogate-assisted evolutionary algorithm for robust design
IEEE Transactions on Evolutionary Computation
Efficient search for robust solutions by means of evolutionary algorithms and fitness approximation
IEEE Transactions on Evolutionary Computation
Using the uncertainty handling CMA-ES for finding robust optima
Proceedings of the 13th annual conference on Genetic and evolutionary computation
| Hi-index | 0.00 |
This paper presents an archive maintenance scheme that can be used within an evaluation scheme for finding robust optima when dealing with expensive objective functions. This archive maintenance scheme aims to select the additional sampling points such that locally well-spread distributions of archive points will be generated. By doing so, the archive will contain better predictive information about the robustness of candidate solutions. Experiments on 10D test problems show that this scheme can be used for accurate local search for robust solutions.