An exact approach for solving integer problems under probabilistic constraints with random technology matrix

Patrizia Beraldi () and Maria Bruni

Annals of Operations Research, 2010, vol. 177, issue 1, 127-137

Abstract: This paper addresses integer programming problems under probabilistic constraints involving discrete distributions. Such problems can be reformulated as large scale integer problems with knapsack constraints. For their solution we propose a specialized Branch and Bound approach where the feasible solutions of the knapsack constraint are used as partitioning rules of the feasible domain. The numerical experience carried out on a set covering problem with random covering matrix shows the validity of the solution approach and the efficiency of the implemented algorithm. Copyright Springer Science+Business Media, LLC 2010

Keywords: Stochastic integer programming; Probabilistic constraints; Branch and bound method (search for similar items in EconPapers)
Date: 2010
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DOI: 10.1007/s10479-009-0670-9

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