Dual decomposition in stochastic integer programming

We present an algorithm for solving stochastic integer programming problems with recourse, based on a dual decomposition scheme and Lagrangian relaxation. The approach can be applied to multi-stage problems with mixed-integer variables in each time stage. Numerical experience is presented for some t...

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Bibliographic Details
Published in:Operations research letters Vol. 24; no. 1; pp. 37 - 45
Main Authors: Carøe, Claus C., Schultz, Rüdiger
Format: Journal Article
Language:English
Published: Amsterdam Elsevier B.V 01.02.1999
Elsevier
Subjects:
Applied sciences
Branch and bound
Exact sciences and technology
Lagrangian relaxation
Mathematical programming
Mixed-integer programming
Operational research and scientific management
Operational research. Management science
Stochastic programming
Branch and bound
Lagrangian relaxation
Mixed-integer programming
Stochastic programming
Mixed integer programming
Duality
Decomposition
Branch and bound method
Convergence
ISSN:0167-6377, 1872-7468
Online Access:Get full text
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Summary:We present an algorithm for solving stochastic integer programming problems with recourse, based on a dual decomposition scheme and Lagrangian relaxation. The approach can be applied to multi-stage problems with mixed-integer variables in each time stage. Numerical experience is presented for some two-stage test problems.
ISSN:0167-6377
1872-7468
DOI:10.1016/S0167-6377(98)00050-9