2026-07-17T21:04:50Z https://drops.dagstuhl.de/oai

oai:drops-oai.dagstuhl.de:2000 2024-03-06T11:08:32Z ddc:004 open_access

A Polynomial Chaos Approach to Robust Multiobjective Optimization Poles, Silvia Lovison, Alberto Uncertainty Quantification Multiobjective Robust Design Monte Carlo Latin Hypercube Polynomial Chaos Robust design optimization is a modeling methodology, combined with a suite of computational tools, which is aimed to solve problems where some kind of uncertainty occurs in the data or in the model. This paper explores robust optimization complexity in the multiobjective case, describing a new approach by means of Polynomial Chaos expansions (PCE). The aim of this paper is to demonstrate that the use of PCE may help and speed up the optimization process if compared to standard approaches such as Monte Carlo and Latin Hypercube sampling. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Silvia Poles and Alberto Lovison 2009 Is Part Of Dagstuhl Seminar Proceedings, Volume 9041, Hybrid and Robust Approaches to Multiobjective Optimization (2009) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/DagSemProc.09041.7 urn:nbn:de:0030-drops-20009 https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.09041.7 eng https://creativecommons.org/licenses/by/4.0/legalcode