Rescue vehicle allocation problem based on optimal reliable path under uncertainty

Consideration of the travel time variation for rescue vehicles is significant in the field of emergency management research. Because of uncertain factors, such as the weather or OD (origin-destination) variations caused by traffic accidents, travel time is a random variable. In emergency situations, it is particularly necessary to determine the optimal reliable route of rescue vehicles from the perspective of uncertainty. This paper first proposes an optimal reliable path finding (ORPF) model for rescue vehicles, which considers the uncertainties of travel time, and link correlations. On this basis, it investigates how to optimize rescue vehicle allocation to minimize rescue time, taking into account travel time reliability under uncertain conditions. Because of the non-additive property of the objective function, this paper adopts a heuristic algorithm based on the K-shortest path algorithm, and inequality techniques to tackle the proposed modified integer programming model. Finally, the numerical experiments are presented to verify the accuracy and effectiveness of the proposed model and algorithm. The results show that ignoring travel time reliability may lead to an over- or under-estimation of the effective travel time of rescue vehicles on a particular path, and thereby an incorrect allocation scheme.

Automated summary

This paper investigates the consideration of travel time variation for rescue vehicles in the field of emergency management research. It proposes an optimal reliable path finding (ORPF) model that takes into account the uncertainties of travel time and link correlations, and explores how to optimize rescue vehicle allocation to minimize rescue time under uncertain conditions. The results highlight the importance of considering travel time reliability in allocation schemes.