Securing Lifelines: Safe Delivery of Critical Services in Areas with Volatile Security Situation via a Stackelberg Game Approach - Mai, Tien; Sinha, Arunesh (Proceedings of the AAAI Conference on Artificial Intelligence, 2023)
Vaccine delivery in under-resourced locations with security risks is not just challenging but also life threatening. The COVID pandemic and the need to vaccinate added even more urgency to this issue. Motivated by this problem, we propose a general framework to set-up limited temporary (vaccination) centers that balance physical security and desired (vaccine) service coverage with limited resources. We set-up the problem as a Stackelberg game between the centers operator (defender) and an adversary, where the set of centers is not fixed a priori but is part of the decision output. This results in a mixed combinatorial and continuous optimization problem. As part of our scalable approximation solution, we provide a fundamental contribution by identifying general duality conditions of switching max and min when both discrete and continuous variables are involved. Via detailed experiments, we show that the solution proposed is scalable in practice.