NSF/USDOT Initiative: Dynamic Cargo Assignment and Route Planning in the Trucking Industy

该项目将研究改进多式联运卡车调度的方法，目的是减少空里程数，改善客户服务。在现实世界中，任何交通网络中的卡车运营都包含相当高的不确定性，包括新订单的到达、现有订单的取消、可变的等待时间和由于交通拥堵而变化的旅行时间。为了充分利用这些技术在卡车运输行业的能力，仍然需要快速高效的算法，能够实时提供良好的解决方案。在这项为期一年的试探性拨款中，重点将放在为有许多支线/最终客户的集中式港口区域服务的卡车调度问题上。这种动态混合求解方法由快速动态规划和搜索技术(如遗传算法)组成。本研究开发的理论和方法可以在以后的几年中扩展以解决更一般的动态路由问题。研究人员将使用包含几个卡车站点、集装箱码头、多式联运设施和最终客户的实际数据来验证动态方法。国际贸易壁垒的消除、更低的关税以及全球制造和消费中心的转移，带来了多式联运的新动态。全球集装箱贸易正以每年9.5%的速度增长，美国的增长率约为6%。预计到2020年，每个主要港口的货运量都将至少翻一番。因此，该国港口附近的卡车交通可能会大幅增长，导致道路拥堵加剧，普通司机和货物进出口都会延误。

This project will investigate methods for improving the scheduling of intermodal trucks with the objective of reducing empty miles improving customer service. In the real world, truck operations in any traffic network contain a fairly high degree of uncertainties including arrival of new orders, cancellation of existing orders, variable waiting times and variable travel times due to traffic congestion. To fully capture the capabilities of these technologies in the trucking industry, quick and efficient algorithms, capable of providing good solutions in real time, are still needed. In this one-year exploratory grant, the focus will be on the problem of scheduling trucks serving a centralized port area with many feeder/end customers. This dynamic hybrid solution methodology consists of a fast dynamic program in conjunction with a search technique (such as genetic algorithms). Theory and methodology developed in this research can be expanded in later years to solve more general dynamic routing problems. The researchers will validate the dynamic approach using actual data that contains several truck depots, container terminals, intermodal facilities and end customers.The elimination of international trade barriers, lower tariffs and shifting centers of global manufacturing and consumption, has lead to new dynamics in intermodal shipping. Worldwide container trade is growing at a 9.5% annual rate, and the U.S. growth rate is around 6%. Every major port is anticipated to at least double its cargo by 2020. As a consequence, truck traffic in the vicinity of the nation's ports is likely to grow substantially, leading to increased roadway congestion, and delays for both ordinary drivers and for the import and export of goods.