Abstract
We consider the problem of dynamically routing a fleet of vehicles tasked with surveilling a set of targets over a collection of waypoints. As motivated by threat detection, the fleet must accrue sufficient coverage on a set of fixed targets while being able to accommodate time-sensitive targets (TSTs) that may become active at a random time during the planning horizon by dynamically adjusting their routes. We propose a Markov decision process model and online routing decision policies based on direct look-ahead strategies via two-stage stochastic programming. We implement the proposed stochastic programming-based look-ahead strategies within a rolling-horizon procedure. Numerical experiment results on a set of benchmark instances show the effectiveness of the proposed approach compared to static routing policies.
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