@inproceedings{e37751b63aa1441b982335f239ceab6f,
title = "Local meta-models for optimization using evolution strategies",
abstract = "We employ local meta-models to enhance the efficiency of evolution strategies in the optimization of computationally expensive problems. The method involves the combination of second order local regression meta-models with the Covariance Matrix Adaptation Evolution Strategy. Experiments on benchmark problems demonstrate that the proposed meta-models have the potential to reliably account for the ranking of the offspring population resulting in significant computational savings. The results show that the use of local meta-models significantly increases the efficiency of already competitive evolution strategies.",
author = "Stefan Kern and Nikolaus Hansen and Petros Koumoutsakos",
year = "2006",
month = jan,
day = "1",
doi = "10.1007/11844297\_95",
language = "English",
isbn = "3540389903",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "939--948",
booktitle = "Parallel Problem Solving from Nature, PPSN IX - 9th International Conference, Procedings",
note = "9th International Conference on Parallel Problem Solving from Nature, PPSN IX ; Conference date: 09-09-2006 Through 13-09-2006",
}