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Udom Janjarassuk (udj2lehigh.edu) Abstract: 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 paper, 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 samplingbased approach to solving the problem. Keywords: Stochastic Network Interdiction, Sample Average Approximation, Computational Grid Category 1: Stochastic Programming Category 2: Applications  OR and Management Sciences (Other ) Citation: Technical Report 06T001, Lehigh University, Department of Industrial and Systems Engineering, January, 2006 Download: [PDF] Entry Submitted: 01/31/2006 Modify/Update this entry  
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