Enhancing a Branch-and-Bound Algorithm for Two-Stage Stochastic Integer Network Design-Based Models

Rafael Andrade (), Abdel Lisser (), Nelson Maculan () and Gérard Plateau ()
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Rafael Andrade: Laboratoire de Recherche en Informatique, Université Paris Sud, Bât 490 Université Paris Sud, 91405 Orsay Cedex, France
Abdel Lisser: Laboratoire de Recherche en Informatique, Université Paris Sud, Bât 490 Université Paris Sud, 91405 Orsay Cedex, France
Nelson Maculan: Universidade Federal do Rio de Janeiro, COPPE-Sistemas, C.P. 68511, 21945-970, Rio de Janeiro, Brazil
Gérard Plateau: LIPN, Institut Galilée, Université Paris Nord, Avenue J.-B. Clément, 93430 Villetaneuse, France

Management Science, 2006, vol. 52, issue 9, 1450-1455

Abstract: In this paper we present branch-and-bound (B& B) strategies for two-stage stochastic integer network design-based models with integrality constraints in the first-stage variables. These strategies are used within L-shaped decomposition-based B& B framework. We propose a valid inequality in order to improve B& B performance. We use this inequality to implement a multirooted B& B tree. A selective use of optimality cuts is explored in the B& B approach and we also propose a subgradient-based technique for branching on 0-1 feasible solutions. Finally, we present computational results for a fixed-charge network design problem with random demands.

Keywords: stochastic integer programming; network design under uncertainty; B& B strategies (search for similar items in EconPapers)
Date: 2006
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:inm:ormnsc:v:52:y:2006:i:9:p:1450-1455

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