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A New Adaptive Algorithm for Convex Quadratic Multicriteria Optimization

Authors: Jörg Fliege, Christoph Heermann, and Bernd Weyers

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


Abstract
We present a new adaptive algorithm for convex quadratic multicriteria optimization. The algorithm is able to adaptively refine the approximation to the set of efficient points by way of a warm-start interior-point scalarization approach. Numerical results show that this technique is an order of magnitude faster than a standard method used for this problem.

Cite as

Jörg Fliege, Christoph Heermann, and Bernd Weyers. A New Adaptive Algorithm for Convex Quadratic Multicriteria Optimization. In Practical Approaches to Multi-Objective Optimization. Dagstuhl Seminar Proceedings, Volume 4461, pp. 1-39, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2005)


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@InProceedings{fliege_et_al:DagSemProc.04461.3,
  author =	{Fliege, J\"{o}rg and Heermann, Christoph and Weyers, Bernd},
  title =	{{A New Adaptive Algorithm for Convex Quadratic Multicriteria Optimization}},
  booktitle =	{Practical Approaches to Multi-Objective Optimization},
  pages =	{1--39},
  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.04461.3},
  URN =		{urn:nbn:de:0030-drops-2386},
  doi =		{10.4230/DagSemProc.04461.3},
  annote =	{Keywords: Multicriteria optimization, warm-start methods, interior-point methods, primal-dual algorithms}
}
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