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Optimal Design of Cordon Sanitaire for Regular Epidemic Control

机译:Cordon Sanitaire定期流行控制的最佳设计

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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.
机译:Covid-19的爆发扰乱了我们的常规生活。许多州和地方当局为保护敏感地区强制执行CORTON SANITAIRE。旅行者只能在合格后穿过港口。本文旨在提出一种方法,以确定在每个入口链路的平行检查点的数量方面确定CORTON SANITAIRE的最佳部署。配方较低级别是通过排队预测业务流入的运输系统均衡的贝芯编程模型,并且上层是排队网络优化,这是一个整数非线性编程。这种优化的目的是最大限度地减少预定的最大等待时间的检查点的总运营成本。注意,随机排队理论用于代表每个条目链路的等待现象。启发式算法旨在解决所提出的Bilevel模型,其中采用了较低级模型采用了连续平均值(MSA)的方法,并采用了遗传算法(GA)的上层模型。进行实验研究以证明所提出的方法和算法的有效性。结果表明,该方法可以找到一个良好的启发式最佳解决方案。这些方法对于政策制定者有用,以确定CORTON SANITAIRE的最佳部署,用于预防和控制。

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