外卖配送路径多目标实时优化研究

随着外卖行业的不断发展，外卖配送的路径优化问题已引起学者们的广泛关注。但现有研究未将骑手的目标考虑在内，且未考虑动态场景下多目标如何设定权重的问题。因此，本文对外卖配送路径的多目标实时优化进行深入研究。建立多目标外卖配送路径优化模型。该模型不仅考虑订单履行时间、平台利润和骑手服务质量3个常用的目标，另外增加骑手等待时间和骑手空驶距离这两个目标，充分将外卖平台、顾客和骑手的目标综合考虑。设计动态调整权重的多目标外卖配送路径启发式算法，解决动态场景下多目标权重如何设定的问题。通过外卖配送的实时数据进行算例分析。结果表明，本文提出的算法可以有效对多目标的外卖配送问题进行实时路径优化，且订单的密集程度对骑手等待时间和订单履行时间有直接的影响。

Multi-objective Real-time Optimization Study of Takeaway Vehicle Routes Problem

With the development of the takeaway industry, the vehicle route problem of takeaway has attracted widespread attention from scholars. However, the existing research does not consider the rider in the objective function and does not consider how to set the weight in the dynamic scene. Therefore, the multi-objective real-time optimization of takeaway delivery routes is studied. Considering the platform, customer and rider in the objective function, a multi-objective takeaway delivery route optimization model is established. A heuristic algorithm for dynamically adjusting the weight of the takeaway delivery route is designed, which solves the problem of setting multi-objective weights in dynamic scenarios. Numerical experiments are carried out on real-time data of takeaway industry. The results show that the algorithm proposed can effectively optimize the real-time route for multi-objective takeaway delivery problems; and the density of orders has a direct impact on rider waiting time and order fulfillment time.