Second-Order Stochastic Dominance Constraints Induced by Mixed-Integer Linear Recourse

Ralf Gollmer; Uwe Gotzes; Rüdiger Schultz

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SPEPS Preprint

Author(s):	Ralf Gollmer, University of Duisburg-Essen Uwe Gotzes, University of Duisburg-Essen Rüdiger Schultz, University of Duisburg-Essen
Title:	Second-Order Stochastic Dominance Constraints Induced by Mixed-Integer Linear Recourse
Date of Acceptance:	03.06.2007
Submission Date:	08.01.2007
Series Title:	Stochastic Programming E-Print Series (SPEPS)
Editors:	Julie L. Higle; Werner Römisch; Surrajeet Sen
Complete Preprint:	pdf (urn:nbn:de:kobv:11-10078091)
Keywords (eng):	stochastic dominance, stochastic integer programming, mixed integer optimization
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Abstract (eng):

We introduce stochastic integer programs with dominance constraints induced by mixed-integer linear recourse. Closedness of the constraint set mapping with respect to perturbations of the underlying probability measure is derived. For discrete probability measures, large-scale, block-structured, mixed-integer linear programming equivalents to the dominance constrained stochastic programs are identiﬁed. For these models, a decomposition algorithm is proposed. Computational tests with instances from power optimization and Sudoku puzzling conclude the paper.

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