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Documents authored by Poles, Silvia

Document
DOI: 10.4230/DagSemProc.09041.5
09041 Working Group on EMO for Robust Multiobjective Optimization (1st Round)

Authors: Joerg Fliege, Nicola Beume, Juergen Branke, Heinrich Braun, Nirupam Chakraborti, Kalyanmoy Deb, Sabine Helwig, Joshua Knowles, Martin Middendorf, Sanaz Mostaghim, Silvia Poles, Salazar Daniel, Shukla Pradymn, and El-Ghazli Talbi

Published in: Dagstuhl Seminar Proceedings, Volume 9041, Hybrid and Robust Approaches to Multiobjective Optimization (2009)

Abstract
This group explored various robust methodologies for multiobjective optimization.
Cite as

Joerg Fliege, Nicola Beume, Juergen Branke, Heinrich Braun, Nirupam Chakraborti, Kalyanmoy Deb, Sabine Helwig, Joshua Knowles, Martin Middendorf, Sanaz Mostaghim, Silvia Poles, Salazar Daniel, Shukla Pradymn, and El-Ghazli Talbi. 09041 Working Group on EMO for Robust Multiobjective Optimization (1st Round). In Hybrid and Robust Approaches to Multiobjective Optimization. Dagstuhl Seminar Proceedings, Volume 9041, pp. 1-5, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2009)

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@InProceedings{fliege_et_al:DagSemProc.09041.5,
  author =	{Fliege, Joerg and Beume, Nicola and Branke, Juergen and Braun, Heinrich and Chakraborti, Nirupam and Deb, Kalyanmoy and Helwig, Sabine and Knowles, Joshua and Middendorf, Martin and Mostaghim, Sanaz and Poles, Silvia and Salazar Daniel and Shukla Pradymn and Talbi, El-Ghazli},
  title =	{{09041 Working Group on EMO for Robust Multiobjective Optimization (1st Round)}},
  booktitle =	{Hybrid and Robust Approaches to Multiobjective Optimization},
  pages =	{1--5},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2009},
  volume =	{9041},
  editor =	{Kalyanmoy Deb and Salvatore Greco and Kaisa Miettinen and Eckart Zitzler},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.09041.5},
  URN =		{urn:nbn:de:0030-drops-20030},
  doi =		{10.4230/DagSemProc.09041.5},
  annote =	{Keywords: Robust multiobjective optimization}
}
Document
DOI: 10.4230/DagSemProc.09041.7
A Polynomial Chaos Approach to Robust Multiobjective Optimization

Authors: Silvia Poles and Alberto Lovison

Published in: Dagstuhl Seminar Proceedings, Volume 9041, Hybrid and Robust Approaches to Multiobjective Optimization (2009)

Abstract
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.
Cite as

Silvia Poles and Alberto Lovison. A Polynomial Chaos Approach to Robust Multiobjective Optimization. In Hybrid and Robust Approaches to Multiobjective Optimization. Dagstuhl Seminar Proceedings, Volume 9041, pp. 1-15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2009)

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@InProceedings{poles_et_al:DagSemProc.09041.7,
  author =	{Poles, Silvia and Lovison, Alberto},
  title =	{{A Polynomial Chaos Approach to Robust Multiobjective Optimization}},
  booktitle =	{Hybrid and Robust Approaches to Multiobjective Optimization},
  pages =	{1--15},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2009},
  volume =	{9041},
  editor =	{Kalyanmoy Deb and Salvatore Greco and Kaisa Miettinen and Eckart Zitzler},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.09041.7},
  URN =		{urn:nbn:de:0030-drops-20009},
  doi =		{10.4230/DagSemProc.09041.7},
  annote =	{Keywords: Uncertainty Quantification, Multiobjective Robust Design, Monte Carlo, Latin Hypercube, Polynomial Chaos}
}
Document
DOI: 10.4230/DagSemProc.04461.15
NBI and MOGA-II, two complementary algorithms for Multi-Objective optimizations

Authors: Enrico Rigoni and Silvia Poles

Published in: Dagstuhl Seminar Proceedings, Volume 4461, Practical Approaches to Multi-Objective Optimization (2005)

Abstract
The NBI-NLPQLP optimization method is tested on several multi-objective optimization problems. Its performance is compared to that of MOGA-II: since NBI-NLPQLP is based on the classical gradient-based NLPQLP, it is fast and accurate, but not as robust, in comparison with the genetic algorithm. Furthermore a discontinuous Pareto frontier can give rise to problems in the NBI´s convergence. In order to overcome this problem, a hybridization technique coupled with a partitioning method is proposed.
Cite as

Enrico Rigoni and Silvia Poles. NBI and MOGA-II, two complementary algorithms for Multi-Objective optimizations. In Practical Approaches to Multi-Objective Optimization. Dagstuhl Seminar Proceedings, Volume 4461, pp. 1-22, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2005)

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@InProceedings{rigoni_et_al:DagSemProc.04461.15,
  author =	{Rigoni, Enrico and Poles, Silvia},
  title =	{{NBI and MOGA-II, two complementary algorithms for Multi-Objective optimizations}},
  booktitle =	{Practical Approaches to Multi-Objective Optimization},
  pages =	{1--22},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2005},
  volume =	{4461},
  editor =	{J\"{u}rgen Branke and Kalyanmoy Deb and Kaisa Miettinen and Ralph E. Steuer},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.04461.15},
  URN =		{urn:nbn:de:0030-drops-2728},
  doi =		{10.4230/DagSemProc.04461.15},
  annote =	{Keywords: Genetic Algorithms, Normal-Boundary Intersection, Designs optimizations}
}
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