{"department":[{"_id":"34"},{"_id":"819"}],"type":"conference","citation":{"ama":"Kerschke P, Preuss M, Wessing S, Trautmann H. Low-Budget Exploratory Landscape Analysis on Multiple Peaks Models. In: Proceedings of the 18$^th$ Annual Conference on Genetic and Evolutionary Computation. ; 2016:229–236. doi:10.1145/2908812.2908845","bibtex":"@inproceedings{Kerschke_Preuss_Wessing_Trautmann_2016, place={Denver, CO, USA}, title={Low-Budget Exploratory Landscape Analysis on Multiple Peaks Models}, DOI={10.1145/2908812.2908845}, booktitle={Proceedings of the 18$^th$ Annual Conference on Genetic and Evolutionary Computation}, author={Kerschke, Pascal and Preuss, Mike and Wessing, Simon and Trautmann, Heike}, year={2016}, pages={229–236} }","ieee":"P. Kerschke, M. Preuss, S. Wessing, and H. Trautmann, “Low-Budget Exploratory Landscape Analysis on Multiple Peaks Models,” in Proceedings of the 18$^th$ Annual Conference on Genetic and Evolutionary Computation, 2016, pp. 229–236, doi: 10.1145/2908812.2908845.","apa":"Kerschke, P., Preuss, M., Wessing, S., & Trautmann, H. (2016). Low-Budget Exploratory Landscape Analysis on Multiple Peaks Models. Proceedings of the 18$^th$ Annual Conference on Genetic and Evolutionary Computation, 229–236. https://doi.org/10.1145/2908812.2908845","mla":"Kerschke, Pascal, et al. “Low-Budget Exploratory Landscape Analysis on Multiple Peaks Models.” Proceedings of the 18$^th$ Annual Conference on Genetic and Evolutionary Computation, 2016, pp. 229–236, doi:10.1145/2908812.2908845.","short":"P. Kerschke, M. Preuss, S. Wessing, H. Trautmann, in: Proceedings of the 18$^th$ Annual Conference on Genetic and Evolutionary Computation, Denver, CO, USA, 2016, pp. 229–236.","chicago":"Kerschke, Pascal, Mike Preuss, Simon Wessing, and Heike Trautmann. “Low-Budget Exploratory Landscape Analysis on Multiple Peaks Models.” In Proceedings of the 18$^th$ Annual Conference on Genetic and Evolutionary Computation, 229–236. Denver, CO, USA, 2016. https://doi.org/10.1145/2908812.2908845."},"user_id":"15504","publication_identifier":{"isbn":["978-1-4503-4206-3"]},"author":[{"full_name":"Kerschke, Pascal","last_name":"Kerschke","first_name":"Pascal"},{"full_name":"Preuss, Mike","last_name":"Preuss","first_name":"Mike"},{"last_name":"Wessing","full_name":"Wessing, Simon","first_name":"Simon"},{"full_name":"Trautmann, Heike","last_name":"Trautmann","id":"100740","first_name":"Heike","orcid":"0000-0002-9788-8282"}],"year":"2016","date_created":"2023-08-04T15:14:06Z","doi":"10.1145/2908812.2908845","status":"public","_id":"46367","abstract":[{"text":"When selecting the best suited algorithm for an unknown optimization problem, it is useful to possess some a priori knowledge of the problem at hand. In the context of single-objective, continuous optimization problems such knowledge can be retrieved by means of Exploratory Landscape Analysis (ELA), which automatically identifies properties of a landscape, e.g., the so-called funnel structures, based on an initial sample. In this paper, we extract the relevant features (for detecting funnels) out of a large set of landscape features when only given a small initial sample consisting of 50 x D observations, where D is the number of decision space dimensions. This is already in the range of the start population sizes of many evolutionary algorithms. The new Multiple Peaks Model Generator (MPM2) is used for training the classifier, and the approach is then very successfully validated on the Black-Box Optimization Benchmark (BBOB) and a subset of the CEC 2013 niching competition problems.","lang":"eng"}],"publication":"Proceedings of the 18$^th$ Annual Conference on Genetic and Evolutionary Computation","title":"Low-Budget Exploratory Landscape Analysis on Multiple Peaks Models","date_updated":"2023-10-16T13:38:47Z","place":"Denver, CO, USA","language":[{"iso":"eng"}],"page":"229–236"}