{"date_created":"2023-08-04T16:07:48Z","date_updated":"2023-10-16T13:56:48Z","editor":[{"first_name":"Robert","last_name":"Schaefer","full_name":"Schaefer, Robert"},{"full_name":"Cotta, Carlos","last_name":"Cotta","first_name":"Carlos"},{"full_name":"Kołodziej, Joanna","last_name":"Kołodziej","first_name":"Joanna"},{"first_name":"Günter","last_name":"Rudolph","full_name":"Rudolph, Günter"}],"type":"conference","publication_identifier":{"isbn":["978-3-642-15871-1"]},"department":[{"_id":"34"},{"_id":"819"}],"status":"public","author":[{"full_name":"Voß, Thomas","last_name":"Voß","first_name":"Thomas"},{"last_name":"Trautmann","orcid":"0000-0002-9788-8282","full_name":"Trautmann, Heike","id":"100740","first_name":"Heike"},{"last_name":"Igel","full_name":"Igel, Christian","first_name":"Christian"}],"abstract":[{"lang":"eng","text":"Since many real-world optimization problems are noisy, vector optimization algorithms that can cope with noise and uncertainty are required. We propose new, robust selection strategies for evolutionary multi-objective optimization in the presence of noise. We apply new measures of uncertainty for estimating the recently introduced Pareto-dominance for uncertain and noisy environments (PDU). The first measure is the inter-quartile range of the outcomes of repeated function evaluations. The second is based on axis-aligned bounding boxes around the upper and lower quantiles of the sampled fitness values in objective space. Experiments on real and artificial problems show promising results."}],"language":[{"iso":"eng"}],"place":"Berlin, Heidelberg","doi":"https://doi.org/10.1007/978-3-642-15871-1_27","user_id":"15504","publication":"Parallel Problem Solving from Nature, PPSN XI","publisher":"Springer Berlin Heidelberg","citation":{"short":"T. Voß, H. Trautmann, C. Igel, in: R. Schaefer, C. Cotta, J. Kołodziej, G. Rudolph (Eds.), Parallel Problem Solving from Nature, PPSN XI, Springer Berlin Heidelberg, Berlin, Heidelberg, 2010, pp. 260–269.","apa":"Voß, T., Trautmann, H., & Igel, C. (2010). New Uncertainty Handling Strategies in Multi-objective Evolutionary Optimization. In R. Schaefer, C. Cotta, J. Kołodziej, & G. Rudolph (Eds.), Parallel Problem Solving from Nature, PPSN XI (pp. 260–269). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-15871-1_27","chicago":"Voß, Thomas, Heike Trautmann, and Christian Igel. “New Uncertainty Handling Strategies in Multi-Objective Evolutionary Optimization.” In Parallel Problem Solving from Nature, PPSN XI, edited by Robert Schaefer, Carlos Cotta, Joanna Kołodziej, and Günter Rudolph, 260–269. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. https://doi.org/10.1007/978-3-642-15871-1_27.","ama":"Voß T, Trautmann H, Igel C. New Uncertainty Handling Strategies in Multi-objective Evolutionary Optimization. In: Schaefer R, Cotta C, Kołodziej J, Rudolph G, eds. Parallel Problem Solving from Nature, PPSN XI. Springer Berlin Heidelberg; 2010:260–269. doi:https://doi.org/10.1007/978-3-642-15871-1_27","mla":"Voß, Thomas, et al. “New Uncertainty Handling Strategies in Multi-Objective Evolutionary Optimization.” Parallel Problem Solving from Nature, PPSN XI, edited by Robert Schaefer et al., Springer Berlin Heidelberg, 2010, pp. 260–269, doi:https://doi.org/10.1007/978-3-642-15871-1_27.","ieee":"T. Voß, H. Trautmann, and C. Igel, “New Uncertainty Handling Strategies in Multi-objective Evolutionary Optimization,” in Parallel Problem Solving from Nature, PPSN XI, 2010, pp. 260–269, doi: https://doi.org/10.1007/978-3-642-15871-1_27.","bibtex":"@inproceedings{Voß_Trautmann_Igel_2010, place={Berlin, Heidelberg}, title={New Uncertainty Handling Strategies in Multi-objective Evolutionary Optimization}, DOI={https://doi.org/10.1007/978-3-642-15871-1_27}, booktitle={Parallel Problem Solving from Nature, PPSN XI}, publisher={Springer Berlin Heidelberg}, author={Voß, Thomas and Trautmann, Heike and Igel, Christian}, editor={Schaefer, Robert and Cotta, Carlos and Kołodziej, Joanna and Rudolph, Günter}, year={2010}, pages={260–269} }"},"title":"New Uncertainty Handling Strategies in Multi-objective Evolutionary Optimization","_id":"46409","year":"2010","page":"260–269"}