Study of Receptive Spot Delivery Routing Problem based on Adaptive Large-scale Neighbor Search Algorithm

摘要

With the frequent occurrence of natural disasters in recent years, emergency logistics and transportation have great significance. The optimization of the vehicle delivery route after disasters is a problem limited by capacity, time window, and cost. We construct a multi-objective model that considers the time window penalty cost to minimize the total costs and maximize the average satisfaction of the disaster sites during the delivery process. Then, we transfer the proposed multi-objective model to a single objective model. Last, an adaptive large neighborhood search (ALNS) algorithm is presented to solve this problem and the experimental results show that the algorithm achieves a high-quality solution on large-scale instances.