Publication Type

Conference Proceeding Article

Version

acceptedVersion

Publication Date

2-2023

Abstract

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.

Keywords

Vaccine delivery, Stackelberg game, mixed integer program, polynomial time heuristic

Discipline

Artificial Intelligence and Robotics | Information Security

Research Areas

Intelligent Systems and Optimization

Publication

Proceedings of the 37th AAAI Conference on Artificial Intelligence, Washington, DC, 2023 February 7-14

First Page

10

Last Page

15

Publisher

AAAI Press

City or Country

Palo Alto, CA

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