Planning of reliable targeted evacuation under the threat of disasters

In planning evacuation services against the threat of disasters, it is important to optimize pickup point location and rescue vehicle routing decisions while recognizing the risks of service disruptions. In this paper, a reliable location and routing model with backup service plans is proposed to plan targeted strategic evacuation, which minimizes the total expected cost for deployment of pickup stations, rescue vehicle routing, and evacuee assignments and exposure while the service is subject to probabilistic disruptions. We formulate the problem as a mixed-integer non-linear program, and develop two customized solution algorithms, one based on Lagrangian relaxation (LR) and the other based on meta-heuristic, to decompose and solve the problem. Numerical experiments with various parameters are conducted to not only demonstrate the applicability of the proposed model and effectiveness of the solution algorithms, but also to draw managerial insights. The impacts of demand distribution, facility cost, disruption probability, and evacuee exposure risk are assessed in a series of sensitivity analyses, so as to inform agencies how to carefully consider these factors while developing a reliable targeted evacuation service plan.