Network flow interdiction on planar graphs
Discrete Applied Mathematics
The $N-k$ Problem in Power Grids: New Models, Formulations, and Numerical Experiments
SIAM Journal on Optimization
The impact of sampling methods on bias and variance in stochastic linear programs
Computational Optimization and Applications
Operations Research Letters
Overlapping batches for the assessment of solution quality in stochastic programs
Proceedings of the Winter Simulation Conference
Maximum dynamic network flow interdiction problem: New formulation and solution procedures
Computers and Industrial Engineering
Computers and Operations Research
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The network interdiction problem involves interrupting an adversary's ability to maximize flow through a capacitated network by destroying portions of the network. A budget constraint limits the amount of the network that can be destroyed. In this article, we study a stochastic version of the network interdiction problem in which the successful destruction of an arc of the network is a Bernoulli random variable, and the objective is to minimize the maximum expected flow of the adversary. Using duality and linearization techniques, an equivalent deterministic mixed integer program is formulated. The structure of the reformulation allows for the application of decomposition techniques for its solution. Using a parallel algorithm designed to run on a distributed computing platform known as a computational grid, we give computational results showing the efficacy of a sampling-based approach to solve the problem. © 2008 Wiley Periodicals, Inc. NETWORKS, 2008