Abstract
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 optimization 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 research uses 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.
Highlights
In the urgent handling of public health emergencies, the medical resources, including protective equipments, disinfection materials, drugs, and medical supplies, are the material basis [1]
We develop a GPHH with the new recourse strategy to design routing policies for multivehicle uncertain CARP (UCARP)
The “(−)” means that the compared algorithms (i.e., GPHH or GPHH-Re) perform significantly worse than GPHH-OneFAll; otherwise, there is no significant difference between the two algorithms
Summary
In the urgent handling of public health emergencies, the medical resources, including protective equipments, disinfection materials, drugs, and medical supplies, are the material basis [1]. The pharmacies, quarantine offices, and community offices can be seen as demand points along the streets in the road network, which correspond to tasks in CARP. A fleet of equipped vehicles is appointed to meet the demands of these points, and both the vehicles that can be dispatched and their capacities are limited, which can be modeled as constraints in CARP. A fleet of vehicles with a limited capacity Q is located at a special vertex called depot v0 ∈ V at the beginning. The goal of the problem is to find out a least-cost routing plan for the vehicles to serve all the tasks subject to the following constraints: 1. Each vehicle starts from the depot and comes back to the depot after serving all the tasks allocated to it. Vehicles can replenish its capacity each time when they pass by the depot
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