Optimizing the aerodynamic efficiency of intermodal freight trains

Yung-Cheng Lai, Christopher P.L. Barkan, Hayri Önal
2008 Transportation Research Part E: Logistics and Transportation Review  
We develop an aerodynamic loading assignment model for intermodal freight trains based on an integer-programming framework to help terminal managers make up more fuel-efficient trains. This is the first use of optimization modeling to address the aerodynamics and energy efficiency of railroad intermodal trains. Several recommendations regarding railway equipment use, operations, and policy are proposed to improve fuel-efficiency and reduce emissions from intermodal transportation. Analysis of
more » ... e major railroad intermodal route reveals the potential to reduce fuel consumption by 15 million gallons per year with corresponding savings of $28,000,000. Greater benefits are possible through broader implementation of the model. Transportation Research Part E 44 (2008) 820-834 www.elsevier.com/locate/tre 70 mph making them the fastest freight trains in North America, thus aerodynamic drag is a particularly important factor affecting their fuel consumption. Lai and Barkan (2005) conducted a series of analyses to compare both the relative and absolute effects of different loading patterns and operating practices on train make-up and energy efficiency. They found that aerodynamic characteristics significantly affect IM train fuel efficiency; and, a train can be more efficiently operated if loads are assigned not only based on slot utilization but also by properly assigning loads to cars, which they referred to as "slot efficiency". Depending on the particular train configuration, train resistance for a fully loaded train can be reduced by as much as 27%, and fuel savings by 1 gallon per mile per train, simply by better matching loads and railcars. Lai and Barkan's previous work (2005) quantified the aerodynamic and energy penalties of specific load and car combinations under idealized conditions. They did not consider the actual make-up of train consists or the wide variety in available loads and car types that a terminal manager must contend with in trying to implement more energy efficient loading practices. Lai et al. (2007) describe a wayside machine vision system that automatically monitors the gap lengths between IM loads on passing trains so the railroad can evaluate the aerodynamic efficiency of their loading pattern. However, no previous work has addressed the question of how to select among the wide variety of loads and railcars actually available to load aerodynamically efficient trains. This is an essential element of achieving the potential fuel and costs savings. In this paper, we develop an aerodynamic loading assignment model (ALAM) using an integer programming (IP) framework to optimize aerodynamic efficiency under various constraints regarding loading assignments. The model can help terminal managers load trains more efficiently and can be incorporated into software used to automate or expedite the loading process inside IM terminals. Previous researchers have considered various other aspects regarding optimization of the loading process and equipment utilization. Feo and Gonzales-Velrade (1995) proposed an integer-linear programming model to maximize the utilization of trailers to railcar hitches. Powell and Carvalho (1998) developed a dynamic model to optimize the flow of flat cars over a network. Corry and Kozan (2006) presented an assignment model to dynamically assign containers to IM trains so as to minimize excess handling time and optimize the weight distribution of the train. Each of the above studies focused on certain types of IM loads or railcars. However, none of them considered the energy efficiency of IM train loading. In this paper, we present the first application of optimization techniques to improve the energy efficiency of IM trains. The proposed model can deal with all types of IM loads (11 different types of trailers and containers), and railcars (hundreds of different types of well, spine, flat cars) operated in North America (TTX Company, 1999). This study is particularly timely in light of increasing fuel prices and their impact on industry operating costs, as well as the need to conserve energy and reduce greenhouse gas emissions. In 2005, the major North American railroads spent over $8 billion on fuel in the United States making it their second largest operating expense. From
doi:10.1016/j.tre.2007.05.011 fatcat:lxtxpykpvzhmlndkeps6mhtcu4