A New Cooperative Recourse Strategy for Emergency Material Allocation in Uncertain Environments - Liu, Yuxin; Wang, Songxin; Li, Xianghua (Frontiers in Physics, 2022)
Emergency material allocation is an important issue in the urgent handling of public health emergencies. This article models the relief allocation and transportation route planning as an uncertain capacitated arc routing problem, which is a classic combinatorial optimisation problem that considers stochastic factors such as uncertain demand and travel time in the service. The stochastic of demand leads to the route failure that the vehicle cannot serve the tasks successfully unexpected. Most existing researches use the independent recourse strategy. That is each vehicle takes a back-and-forth trip separately when its remaining capacity cannot meet the actual demand of the task. This leads to a considerable recourse cost. However, a few studies have considered vehicular cooperation to deal with route failure, which is beneficial for pooling the capacity of multiple vehicles. In this paper, we propose a new recourse strategy called OneFAll that lets one vehicle take charge of all the failed tasks. In this case, other vehicles can finish the service once they are full. We develop the genetic programming hyper-heuristic with the OneFAll recourse strategy for solving the uncertain capacitated arc routing problem. The experimental studies show that our proposed method outperforms the existing genetic programming hyper-heuristic with the independent recourse strategy to the uncertain capacitated arc routing problem for the ugdb and uval benchmark instances. Moreover, our strategy outperforms the recourse strategy that failed tasks are returned to the unassigned task set for any vehicle to complete. This reflects that there exists resource waste if all vehicles are involved to repair the failed routes.