## Abstract

A simultaneous non-zero-sum game is modeled to extend the classical network interdiction problem. In this model, an interdictor (e.g., an enforcement agent) decides how much of an inspection resource to spend along each arc in the network to capture a smuggler. The smuggler (randomly) selects a commodity to smuggle—a source and destination pair of nodes, and also a corresponding path for traveling between the given pair of nodes. This model is motivated by a terrorist organization that can mobilize its human, financial, or weapon resources to carry out an attack at one of several potential target destinations. The probability of evading each of the network arcs nonlinearly decreases in the amount of resource that the interdictor spends on its inspection. We show that under reasonable assumptions with respect to the evasion probability functions, (approximate) Nash equilibria of this game can be determined in polynomial time; depending on whether the evasion functions are exponential or general logarithmically-convex functions, exact Nash equilibria or approximate Nash equilibria, respectively, are computed.

Original language | English |
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Pages (from-to) | 139-153 |

Number of pages | 15 |

Journal | Naval Research Logistics |

Volume | 64 |

Issue number | 2 |

DOIs | |

State | Published - Mar 2017 |

### Bibliographical note

Publisher Copyright:© 2017 Wiley Periodicals, Inc.

## Keywords

- Ellipsoid method
- Nash equilibrium
- computational game theory
- convex optimization
- inspection game
- network interdiction
- non-zero-sum game
- resource allocation