Conditioning of linear-quadratic two-stage stochastic optimization problems

In this paper a condition number for linear-quadratic two-stage stochastic optimization problems is introduced as the Lipschitz modulus of the multifunction assigning to a (discrete) probability distribution the solution set of the problem. Being the outer norm of the Mordukhovich coderivative of th...

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Veröffentlicht in:Mathematical programming Jg. 148; H. 1-2; S. 201 - 221
Hauptverfasser: Emich, Konstantin, Henrion, René, Römisch, Werner
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Berlin/Heidelberg Springer Berlin Heidelberg 01.12.2014
Springer Nature B.V
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ISSN:0025-5610, 1436-4646
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Zusammenfassung:In this paper a condition number for linear-quadratic two-stage stochastic optimization problems is introduced as the Lipschitz modulus of the multifunction assigning to a (discrete) probability distribution the solution set of the problem. Being the outer norm of the Mordukhovich coderivative of this multifunction, the condition number can be estimated from above explicitly in terms of the problem data by applying appropriate calculus rules. Here, a chain rule for the extended partial second-order subdifferential recently proved by Mordukhovich and Rockafellar plays a crucial role. The obtained results are illustrated for the example of two-stage stochastic optimization problems with simple recourse.
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ISSN:0025-5610
1436-4646
DOI:10.1007/s10107-013-0734-0