Interdiction of a Markovian evader
- Los Alamos National Laboratory
- CORNELL UNIV
Network interdiction is a combinatorial optimization problem on an activity network arising in a number of important security-related applications. It is classically formulated as a bilevel maximin problem representing an 'interdictor' and an 'evader'. The evader tries to move from a source node to the target node along the shortest or safest path while the interdictor attempts to frustrate this motion by cutting edges or nodes. The interdiction objective is to find the optimal set of edges to cut given that there is a finite interdiction budget and the interdictor must move first. We reformulate the interdiction problem for stochastic evaders by introducing a model in which the evader follows a Markovian random walk guided by the least-cost path to the target. This model can represent incomplete knowledge about the evader and the graph as well as partial interdiction. We formulate the optimization problem for this model and show how, by exploiting topological ordering of the nodes, one can achieve an order-of-magnitude speedup in computing the objective function. We also introduce an evader-motion-based heuristic that can significantly improve solution quality by providing a global view of the network to approximation methods.
- Research Organization:
- Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
- Sponsoring Organization:
- USDOE
- DOE Contract Number:
- AC52-06NA25396
- OSTI ID:
- 960923
- Report Number(s):
- LA-UR-08-06551; LA-UR-08-6551; TRN: US201008%%828
- Resource Relation:
- Conference: Alenex 09 Workshop on Algorithm Engineering and Experiments ; January 3, 2009 ; New York, NY
- Country of Publication:
- United States
- Language:
- English
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