LCEVES: A locally constrained evolutionary algorithm for vehicle evacuation scheduling under urban waterlogging risk

The global rising level of climate change has caused significant disruptions in city traffic patterns due to intense heavy rains causing urban waterlogging disasters worldwide. These disasters have also resulted in massive economic losses and casualties. In consideration of these issues, the current challenge for urban disaster emergency response is to determine strategies to arrange for emergency vehicle scheduling as soon as urban waterlogging expands in a way that minimizes casualties and financial losses. This article proposes the Locally Constraint Evolutionary algorithm for Vehicle Evacuation Scheduling (LCEVES), which includes the following features to address the vehicle emergency evacuation problems in urban waterlogging zones specifically for regulated vehicles (e.g., buses, vehicles transporting hazardous materials, etc.). Firstly, a general technical route for vehicle emergency evacuation under urban waterlogging risk, secondly an optional routes search mechanism for vehicle evacuation in the waterlogging area and thirdly a locally constraint evolutionary algorithm for vehicle evacuation in the waterlogging area. The experiments show that LCEVES improves vehicle evacuation efficiency and reduces the risk of affected vehicles, providing an effective means for vehicle evacuation in the waterlogging zone. This research provides an effective method for solving vehicle evacuation scheduling challenges during urban waterlogging and also has significance for vehicle scheduling in other types of disasters.