The outbreak of COVID-19 has disrupted our regular life. Many state and local authorities have enforced a cordon sanitaire for the protection of sensitive areas. Travelers can only travel across the cordon after qualified. This paper aims to propose a method to determine the optimal deployment of cordon sanitaire in terms of the number of parallel checkpoints at each entry link. A two-stage model is formulated where the first stage is the transportation system equilibrium to predict traffic inflow, and the second stage is queueing network optimization, which is an integer nonlinear programming. The objective of this optimization is to minimize the total operation cost of checkpoints with a predetermined maximum waiting time. Note that queueing theory is used to represent the waiting phenomenon at each entry link. A heuristic algorithm is designed to solve the proposed two-stage model where the method of successive averages (MSA) is adopted for the first stage, and the genetic algorithm (GA) is adopted for the second stage. An experimental study is conducted to demonstrate the effectiveness of the proposed method and algorithm. The results show that the methods can find a good heuristic optimal solution. These methods are useful for policymakers to determine the optimal deployment of cordon sanitaire for disease prevention and control.

CICTP