This paper presents a new approach for formulating the delivery problem by drones with general energy consumption models where the drones visit a set of places to deliver parcels to customers. Drones can perform multiple trips that start and end at a central depot while visiting several customers along their paths. The problem determines the routing and scheduling decisions of the drones in order to minimize the total transportation cost of serving customers. For the first time, the new formulation approach enables us to use the best available energy consumption model without the need of any extra approximations. Though the approach works in a very general setting including non-convex energy consumption models, it is also computationally efficient as the resulting optimization model has a linear relaxation. A numerical study on 255 benchmark instances with up to 50 customers and a specific energy function indicate that all the instances can be solved 20 times faster on average using the new formulation when compared to the best existing branch-and-cut algorithm. All the 15 benchmark instances with 50 customers are solved exactly, whereas none of them has been solved optimally before. Moreover, new instances with up to 150 customers are solved with small error bounds within a few hours. The new approach can be simply applied to consider the extra energy required when a drone needs to continue hovering until opening the delivery time window. It can also be applied to the case where the flight time is dependent on the drone's payload weight. Owing to the flexibility of the new approach, these challenging extensions are formulated as linear optimization models for the first time.
翻译:本文提出了一种新方法,用通用能源消费模式来分析无人机的运送问题,无人机在这种模式下访问一组地方向客户运送包裹。无人机可以进行多次旅行,在中央仓库开始和结束的多次旅行,同时沿途访问几个客户。这个问题决定了无人机的路线和时间安排决定,以尽量减少服务客户的总运输费用。第一次,新的拟订方法使我们能够使用现有的最佳能源消费模式,而不需要任何额外的近似值。虽然该方法在包括非康维克斯能源消费模式在内的一个非常笼统的环境下运作,但它也具有计算效率,因为由此产生的优化模式具有线性放松。对255个基准案例进行的数字研究显示,最多有50个客户和具体能源功能,表明所有案例都可以平均以20倍的速度通过新公式解决,以尽量减少服务客户的运输费用。所有有50个客户的15个基准案例都完全解决了,而其中没有一个是以前最理想地解决的。此外,最多150个客户的新案例可以在几个小时内以小的错误来解决,因为由此产生的优化模式有线性宽宽宽。新的办法可以适用于飞行时段,因此,在考虑飞行机头头头需要时,因此需要采用新的飞行机的机压。