A Dynamic Vehicle Routing Problem for Responding to Large-Scale Emergencies

In this paper, we propose a mathematical model for a dynamic vehicle routing problem (VRP) to minimize unmet demand with stochastic demands and real-time vehicle control in large-scale emergencies. In this context, we consider that one depot may not supply all demand nodes with sufficient medicine that they need in limited time. The problem involves multiple vehicles with various capacities and instantaneous variations of service requests in demand nodes. Both dispatched (serving on a route) and undispatched (at the depot) vehicles are considered in the problem. And the route adjustments arising from new or reduced demand nodes and various service requests are also considered. Then, we propose a hybrid solution algorithm based on C-W saving and tabu search algorithms to solve the proposed model. Finally, experiments demonstrate the effectiveness of the proposed model and algorithm.