DagSemProc.04461.3.pdf
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A New Adaptive Algorithm for Convex Quadratic Multicriteria Optimization
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Dagstuhl Seminar Proceedings, Volume 4461
Series: Dagstuhl Seminar Proceedings (DagSemProc) - License:
Creative Commons Attribution 4.0 International license
- Publication Date: 2005-08-10
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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)
https://doi.org/10.4230/DagSemProc.04461.3
https://doi.org/10.4230/DagSemProc.04461.3
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.
Keywords
- Multicriteria optimization
- warm-start methods
- interior-point methods
- primal-dual algorithms
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