论文标题

合并乘客和货运运输的模块化车辆路线

Modular Vehicle Routing for Combined Passenger and Freight Transport

论文作者

Hatzenbühler, Jonas, Jenelius, Erik, Gidófalvi, Győző, Cats, Oded

论文摘要

城市交付的持续增长和大型城市的持续城市化需要开发高效且可持续的运输解决方案。这项研究调查了模块化车辆概念的影响以及不同需求类型在路线计划中对城市货运和客运系统效率的巩固。通过将多个车辆连接在一起形成排,可以实现模块化。通过同时考虑优化算法中的乘客和货运需求,可以实现不同需求类型的合并。所考虑的车辆对每种需求类型都是特定的,因此可以自由连接,因此可以在同一排中运输不同的需求类型。问题配方中的成本条款包括旅行时间成本,旅行距离成本,车队的规模成本以及考虑无关请求的成本。模块化车辆操作是在新型的拾取和交付问题中建模的,该问题是通过CPLEX和自适应大型邻里搜索来解决的。在斯德哥尔摩的广泛情景研究和案例研究中,对于不同的空间和时间需求分布,探索了新的模块化车辆类型的潜力。对车辆容量,车辆范围和节省成本假设的参数研究进行了研究,以研究其对效率的影响。进行实验表明,由于模块化,一般成本节省了48%,由于合并而额外的9%。减少主要来自降低的运营成本和降低的行程持续时间,而在所有情况下都可以提出相同数量的请求。通过巩固和模块化,空的车辆公里数减少了60%以上。公司和政策制定者可以使用所提出的模型和优化框架来确定所需的车队尺寸,最佳车辆路线和成本节省。

The continuous increase in urban deliveries and the ongoing urbanization of large cities require the development of efficient and sustainable transportation solutions. This study investigates the impact of modular vehicle concepts and the consolidation of different demand types in the route planning on the efficiency of the urban freight and passenger transportation system. Modularity is achieved by connecting multiple vehicles together to form a platoon. The consolidation of different demand types is realized by simultaneously consider passenger and freight demand in the optimization algorithm. The considered vehicles are specific for each demand type by can be connected freely, hence it is possible to transport different demand types in the same platoon. The cost terms in the problem formulation are comprised of travel time costs, travel distance costs, fleet size costs, and cost considering unserved requests. The modular vehicle operations are modeled in a novel pickup and delivery problem which is solved using CPLEX and Adaptive Large Neighborhood Search. In an extensive scenario study and case study in Stockholm, the potentials of the new modular vehicle type are explored for different spatial and temporal demand distributions. A parameter study on vehicle capacity, vehicle range and cost saving assumptions is performed to study their influence on the efficiency. The experiments carried out indicate a general cost savings of 48% due to modularity and an additional 9% due to consolidation. The reduction mainly stems from reduced operating costs and reduced trip duration, while the same number of requests can be served in all cases. Empty vehicle kilometers are reduced by more than 60% by consolidation and modularity. The proposed model and optimization framework can be used by companies and policy makers to identify required fleet sizes, optimal vehicle routes and cost savings.

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