The use of electric buses is expected to rise due to its environmental benefits. However, electric vehicles are less flexible than conventional diesel buses due to their limited driving range and longer recharging times. Therefore, scheduling electric vehicles adds further operational difficulties. Additionally, various labor regulations challenge public transport companies to find a cost-efficient crew schedule. Vehicle and crew scheduling problems essentially define the cost of operations. In practice, these two problems are often solved sequentially. In this paper, we introduce the integrated electric vehicle and crew scheduling problem (E-VCSP). Given a set of timetabled trips and recharging stations, the E-VCSP is concerned with finding vehicle and crew schedules that cover the timetabled trips and satisfy operational constraints, such as limited driving range of electric vehicles and labor regulations for the crew while minimizing total operational cost. An adaptive large neighborhood search that utilizes branch-and-price heuristics is proposed to tackle the E-VCSP. The proposed method is tested on real-life instances from public transport companies in Denmark and Sweden that contain up to 1109 timetabled trips. The heuristic approach provides evidence of improving efficiency of transport systems when the electric vehicle and crew scheduling aspects are considered simultaneously. By comparing to the traditional sequential approach, the heuristic finds improvements in the range of 1.17–4.37% on average. A sensitivity analysis of the electric bus technology is carried out to indicate its implications for the crew schedule and the total operational cost. The analysis shows that the operational cost decreases with increasing driving range (120–250 km) of electric vehicles.

由于其环境效益，电动巴士的使用有望增加。然而，由于电动汽车的有限行驶范围和更长的充电时间，其电动汽车的灵活性不如传统的柴油公交车。因此，调度电动车辆增加了进一步的操作困难。此外，各种劳工法规对公共交通公司提出了挑战，要求他们找到具有成本效益的船员时间表。车辆和人员调度问题从根本上定义了运营成本。实际上，这两个问题通常是相继解决的。在本文中，我们介绍了集成的电动汽车和人员调度问题（E-VCSP）。给定一组时间表的行程和充电站，E-VCSP关心的是查找涵盖时间表的行程并满足运营约束的车辆和机组人员时间表，例如电动汽车的有限行驶范围和船员的劳动法规，同时最大程度地降低了总运营成本。提出了一种利用分支和价格启发式方法的自适应大邻域搜索来解决E-VCSP问题。在丹麦和瑞典的公共交通公司的实际实例中对提出的方法进行了测试，该实例包含最多1109个时间表行程。当同时考虑电动车辆和乘员调度方面时，启发式方法提供了提高运输系统效率的证据。通过与传统的顺序方法进行比较，启发式方法发现平均改善了1.17-4.37％。进行了电动巴士技术的敏感性分析，以表明其对乘务员时间表和总运营成本的影响。