| Abstract: |  Drug smuggling is a worldwide problem with many negative effects on the society. It is important to understand and predict smuggler's behavior in order to best position patrolling assets and disrupt his supply chain. The goal of this thesis is formalize smuggler's behavior and compare it with real-world data. Smuggler's route planner makes the main component of this thesis, it's formalized as bi-objective route optimizer, weighting route length and risk of interception along the route. Agent-based simulation of the problem is formed. Results show that smugglers can be divided into classes according to their willingness to risk.
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