城市配送量的持续增长与大城市的不断城市化，要求开发高效且可持续的交通解决方案。本研究探讨了模块化车辆概念以及路线规划中不同需求类型的整合对城市货运与客运系统效率的影响。模块化通过将多辆车连接形成车队（platoon）来实现，不同需求类型的整合则通过在优化算法中同时考虑客运与货运需求来达成。所研究的车辆虽针对每种需求类型专用，但可自由连接，因此能够在同一车队中运输不同类型的需求。问题公式中的成本项包括行程时间成本、行驶距离成本、车队规模成本以及未服务请求的相关成本。\n我们将模块化车辆运营建模为一种新型取送货问题，采用CPLEX和自适应大邻域搜索（Adaptive Large Neighborhood Search）进行求解。通过在斯德哥尔摩开展的大规模场景研究与案例研究，我们探究了这种新型模块化车辆在不同时空需求分布下的潜力。研究还针对车辆容量、车辆续航里程和成本节约假设开展了参数研究，以分析它们对效率的影响。实验结果表明，模块化可带来48%的总体成本节约，需求整合可额外带来9%的成本节约；成本降低主要源于运营成本减少和行程时长缩短，且所有场景下均可服务相同数量的请求。此外，需求整合与模块化共同作用可将空驶里程减少60%以上。所提出的模型与优化框架可供企业和政策制定者用于确定所需车队规模、最优车辆路线及成本节约量。
英文摘要：
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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Cornell University（康奈尔大学）；University of Illinois at Urbana-Champaign（伊利诺伊大学厄巴纳-香槟分校）；The University of Sydney（悉尼大学）；Sharif University of Technology（谢里夫理工大学）
