This paper investigates the construction of routes over multiple days while maintaining driver consistency, which requires that the multi-day service of each customer be provided by as few different drivers as possible over a planning horizon. Furthermore, if one customer is assigned to different drivers over multiple days, it is desirable that services are provided by one driver on as many days as possible. To optimize this driver consistency, a new quantitative measure of driver consistency is defined. In the proposed vehicle routing problem with driver consistency, driver consistency is modeled in the objective function. Another contribution is that we model the vehicle routing problem with driver consistency considering uncertainties in customer demands, travel times, and service times. Uncertain programming models for the considered problem are developed utilizing uncertainty theory. A hybrid algorithm with large neighborhood search and simulated annealing is designed to address the proposed NP-hard problem. Computational experiments are conducted on several datasets to highlight the performance of the proposed approach and the models. The impacts of uncertainty and the trade-off between the total travel time and driver consistency are also analyzed to reveal some managerial insights.

Our analysis shows that uncertainty has negative impacts on minimizing total travel time while can improve driver consistency in some cases; Remarkable reduction in the total travel time can be achieved with little damage on driver consistency; However, totally focusing on minimizing total travel time comes at the price of sacrificing driver consistency drastically.

本文研究了在保持驾驶员一致性的情况下多天的路线构建，这要求在规划范围内由尽可能少的不同驾驶员提供每个客户的多天服务。此外，如果一个客户在多天内被分配给不同的司机，则希望由一名司机在尽可能多的日子里提供服务。为了优化这种驱动一致性，定义了一种新的驱动一致性定量测量。在提出的具有驾驶员一致性的车辆路径问题中，驾驶员一致性在目标函数中建模。另一个贡献是，我们考虑到客户需求、旅行时间和服务时间的不确定性，对具有驾驶员一致性的车辆路线问题进行建模。利用不确定性理论开发了所考虑问题的不确定性规划模型。设计了一种具有大邻域搜索和模拟退火的混合算法来解决所提出的 NP-hard 问题。在几个数据集上进行了计算实验，以突出所提出的方法和模型的性能。还分析了不确定性的影响以及总行程时间和驾驶员一致性之间的权衡，以揭示一些管理见解。

我们的分析表明，不确定性对减少总行程时间有负面影响，但在某些情况下可以提高司机的一致性；可以显着减少总行程时间，而对驾驶员一致性的损害很小；然而，完全专注于最小化总行程时间的代价是大幅牺牲驾驶员的一致性。