Truck routing and platooning optimization considering drivers’ mandatory breaks
Truck routing and platooning optimization considering drivers’ mandatory breaks
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DOI：
10.1016/j.trc.2022.103809
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发表时间：
2022-10
期刊：
影响因子：
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通讯作者：
Min Xu;Xiaoyuan Yan;Yafeng Yin
中科院分区：
文献类型：
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作者：
Min Xu;Xiaoyuan Yan;Yafeng Yin
卡车车队被吹捧为最有希望提高燃油效率的技术之一，因为在类似火车的车队中，数字连接卡车的滑流减少了空气阻力。卡车车队的好处在于降低了燃料消耗和劳动力成本，并增强了驾驶体验。然而，如果没有一个合适的路线、调度和队列计划的卡车受实际约束，特别是司机的长途旅行的休息需求，这些好处是无法实现的。本研究考虑了司机的强制休息，以及其他特征，如队列的状态和位置相关的节油率，卡车指定的中间继电器和队列大小限制，解决了卡车路线和队列问题。问题是在满足驾驶员休息时间要求的情况下，在整个行程中最大限度地形成节油排，以最少的燃油量将卡车准时送到各自的目的地。首先建立了混合整数线性规划（MILP）模型。为了解决这一问题，提出了一种将部分milp方法和迭代邻域搜索结合定制搜索算子的混合算法。在数值实验中使用了各种随机生成的网络来检验我们所提出的模型和求解方法的有效性和效率。并进行了广泛的敏感性分析，探讨了驾驶员强制休息时间、车队领车燃油减量率以及服务时间窗口宽度等几个主要影响因素对系统性能的影响，得出了管理见解。
Truck platooning has been touted as one of the most promising technologies to improve fuel efficiency thanks to the reduced air drag of the digitally connected truck’s slipstream in a trainlike convoy. The benefits of truck platooning lie in the reduced fuel consumption and labor cost, and the enhanced driving experience. However, these benefits cannot be realized without an appropriate routing, scheduling, and platooning plan of trucks subject to practical constraints, especially the drivers’ break requirement for long-haul journeys. This study addresses the truck routing and platooning problem considering drivers’ mandatory breaks as well as other characteristics such as the state-and-position-dependent fuel-saving rates of platooning, trucks’ designated intermediate relays, and platoon size limit. The problem is to route the trucks to their respective destinations on time using the least amount of fuel by maximizing the formations of fuel-saving platoons over entire trips while satisfying the break time requirement of drivers. A mixed-integer linear programming (MILP) model is first developed for the proposed problem. A hybrid algorithm integrating the partial-MILP approach and iterated neighborhood search with tailored search operators is proposed to address the problem. Various randomly generated networks are used in numerical experiments to examine the effectiveness and efficiency of our proposed model and solution method. An extensive sensitivity analysis is also conducted to explore the impacts of several major influential factors, i.e., the drivers’ mandatory break times, the fuel reduction rate of the leading truck of platoons, as well as the width of the service time window, on the system performance and derive the managerial insights.