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Contribution Details

Type Journal Article
Scope Discipline-based scholarship
Title Some insights into the solution algorithms for SLP problems
Organization Unit
Authors
  • Peter Kall
  • János Mayer
Item Subtype Original Work
Refereed Yes
Status Published in final form
Language
  • English
Journal Title Annals of Operations Research
Publisher Springer
Geographical Reach international
ISSN 0254-5330
Volume 142
Number 1
Page Range 147 - 164
Date 2006
Abstract Text We consider classes of stochastic linear programming problems which can be efficiently solved by deterministic algorithms. For two–stage recourse problems we identify two such classes. The first one consists of problems where the number of stochastically independent random variables is relatively low; the second class is the class of simple recourse problems. The proposed deterministic algorithm is successive discrete approximation. We also illustrate the impact of required accuracy on the efficiency of this algorithm. For jointly chance constrained problems with a random right–hand–side and multivariate normal distribution we demonstrate the increase in efficiency when lower accuracy is required, for a central cutting plane method. We support our argumentation and findings with computational results.
Free access at DOI
Digital Object Identifier 10.1007/s10479-006-6166-y
Other Identification Number merlin-id:3486
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