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

University Of Southern California, Los Angeles CA

Investigators

Abstract

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.