Abstract
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 being 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 for regular epidemic control. A bilevel programming model is formulated where the lower-level is the transport system equilibrium with queueing to predict traffic inflow, and the upper-level 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 stochastic queueing theory is used to represent the waiting phenomenon at each entry link. A heuristic algorithm is designed to solve the proposed bilevel model where the method of successive averages (MSA) is adopted for the lower-level model, and the genetic algorithm (GA) is adopted for the upper-level model. 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 hazard prevention and control.
Highlights
Introduction e COVID19 pandemic is an ongoing pandemic of the coronavirus disease 2019 caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)
A cordon sanitaire is used to restrict the movement of people into and/ or out of a defined geographic area, such as a community, city, or region. e term denoted a barrier used to stop the spread of infectious diseases
It is reported that the queue length is too long, and the waiting cost is too high at the cordon sanitaire. erefore, there is an urgent need to optimize the queueing system to improve the service level of testing. is paper aims to propose a method to deploy checkpoints at the cordon sanitaire to ensure the maximum waiting time
Summary
Equivalently negative exponential interarrival or service time distribution and c means the number of identical parallel servers with same average service rate per unit time. Note that the service level in a given entrance i is a function of the number of parallel checkpoints, ci. E upper-level presents a decision model for determining minimal operation cost considering the acceptable average waiting time di. An integer nonlinear programming model can be proposed where the objective is to minimize the expected total cost of testing operation, the constraint is an aspiration level of the vehicle waiting time at each entrance, and the decision variables are the number of parallel checkpoints in each entrance. Where ci, ∀i ∈ A∗, are decision variables and traffic flows λi, ∀i ∈ A∗, are variables determined by the lower-level model, i.e., network equilibrium model with queueing. Equation (10) is the aspiration level of the vehicle waiting time for each entrance where T is a constant determined by the policymaker. It should be noted that the integer nonlinear programming model is hard to solve by classical optimization methods so that a heuristic algorithm is designed in the followed section
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