Multi‐objective optimization of cordon sanitaire with vehicle waiting time constraint

Abstract

The outbreak of COVID‐19 has disrupted our regular life. Many local authorities have enforced a cordon sanitaire for the protection of sensitive areas. Travelers can only travel across the cordon after getting 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 bi‐level multi‐objective programming model is formulated where the lower‐level is the transportation system equilibrium with queueing to predict link traffic flow, and the upper‐level is queueing network optimization that is a multi‐objective integer non‐linear programming. The primary objective is to minimize the total operation cost of checkpoints with a predetermined waiting time constraint and the secondary objective is to minimize system total travel time. A heuristic algorithm is designed to solve the proposed bi‐level model where the method of successive averages is adopted for the lower‐level model, and a hybrid genetic algorithm is designed for the upper‐level model. An experimental study is conducted to demonstrate the effectiveness of the proposed methods. The results show that the methods can find a good heuristic optimal solution. These methods are useful for operators to determine the optimal deployment of cordon sanitaire.