Lexicographic network interdiction model - Siew, Jun Jie. (2013)
This project describes a lexicographic network interdiction model for identifying optimal locations for equipping patrol guards with detectors sensitive to explosive materials. A risk averse terrorist has a set of targets, each yielding varying degrees of damage when destroyed. The terrorist prioritizes the targets with preference over targets which incur the greatest damage to the interdictor. The interdictor, with full knowledge of the targets and their given priority by the terrorist, deploys patrol teams equipped with detectors to maximise detection probability such that the terrorist will be deterred from the higher priority targets, hence minimizing damage. The problem is stochastic as the interdictor is uncertain about the terrorist’s origin location at the time when the patrol teams with detectors are being deployed. The terrorist is informed, aware of the network probability and the interdicted locations when selecting his path only when he is in the network. The problem is formulated as a bi-level min-max lexicographic network interdiction problem. Both the terrorist and interdictor have multiple objectives and the solution is formulated as a lexicographic optimization problem. The project provides insights to the optimal resource allocation decision by the interdictor based on the formulated model.