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Université de Technologie de Compiègne, Laboratoire Heudiasyc UMR CNRS 6599, 60205 Compiègne Cedex, France
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.
(Received April 17 2007)
(Accepted July 15 2008)
(Online publication April 28 2009)
Mathematics Subject Classification: