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Tractable algorithmsfor chance-constrained combinatorial problems

Published online by Cambridge University Press:  28 April 2009

Olivier Klopfenstein
Olivier Klopfenstein*
Affiliation:
France Télécom R&D, 38-40 rue du gl Leclerc, 92130 Issy-les-Moulineaux, France; olivier.klopfenstein@orange-ftgroup.com Université de Technologie de Compiègne, Laboratoire Heudiasyc UMR CNRS 6599, 60205 Compiègne Cedex, France
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Abstract

This paper aims at proposing tractable algorithms to find effectively good solutions to large size chance-constrained combinatorial problems. A new robust model is introduced to deal with uncertainty in mixed-integer linear problems. It is shown to be strongly related to chance-constrained programming when considering pure 0–1 problems. Furthermore, its tractability is highlighted. Then, an optimization algorithm is designed to provide possibly good solutions to chance-constrained combinatorial problems. This approach is numerically tested on knapsack and multi-dimensional knapsack problems. The results obtained outperform many methods based on earlier literature.

Keywords

Integer linear programmingchance constraintsrobust optimizationheuristic.

Information

Type
Research Article
Information
RAIRO - Operations Research , Volume 43 , Issue 2 , April 2009 , pp. 157 - 187
Copyright
© EDP Sciences, ROADEF, SMAI, 2009

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