An adaptive primal-dual warm-start technique for quadratic multiobjective optimization
An adaptive primal-dual warm-start technique for quadratic multiobjective optimization
We present a new primal-dual 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. Results of this algorithm when applied on a three-criteria real-world power plant optimization problem are reported, thereby illustrating the feasibility of this approach when used in practice.
Molz, Daniel
ce2d5972-bd0b-4927-b1f5-0ba87317ced9
Heermann, Christoph
e62ed7a9-1aa7-4825-877d-abe69cc5f440
Fliege, Jörg
54978787-a271-4f70-8494-3c701c893d98
Molz, Daniel
ce2d5972-bd0b-4927-b1f5-0ba87317ced9
Heermann, Christoph
e62ed7a9-1aa7-4825-877d-abe69cc5f440
Fliege, Jörg
54978787-a271-4f70-8494-3c701c893d98
Molz, Daniel, Heermann, Christoph and Fliege, Jörg
(2006)
An adaptive primal-dual warm-start technique for quadratic multiobjective optimization.
Optimization Online.
(Submitted)
Abstract
We present a new primal-dual 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. Results of this algorithm when applied on a three-criteria real-world power plant optimization problem are reported, thereby illustrating the feasibility of this approach when used in practice.
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Submitted date: 23 September 2006
Organisations:
Operational Research
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Local EPrints ID: 54539
URI: http://eprints.soton.ac.uk/id/eprint/54539
PURE UUID: 366ba916-f28c-40e4-b7cb-2636ca235483
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Date deposited: 28 Jul 2008
Last modified: 12 Dec 2021 03:40
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Contributors
Author:
Daniel Molz
Author:
Christoph Heermann
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