License: Creative Commons Attribution 4.0 International license (CC BY 4.0)
When quoting this document, please refer to the following
DOI: 10.4230/DagSemProc.04461.3
URN: urn:nbn:de:0030-drops-2386
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2005/238/
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Fliege, Jörg ;
Heermann, Christoph ;
Weyers, Bernd
A New Adaptive Algorithm for Convex Quadratic Multicriteria Optimization
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.
BibTeX - Entry
@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/opus/volltexte/2005/238},
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}
}
Keywords: |
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Multicriteria optimization, warm-start methods, interior-point methods, primal-dual algorithms |
Collection: |
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04461 - Practical Approaches to Multi-Objective Optimization |
Issue Date: |
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2005 |
Date of publication: |
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10.08.2005 |