Future Substitutes for Diesel Fuel in U.S. Truck and Railroad Freight Transportation

This paper explains why diesel fuel is the preferred fuel in freight transportation. It identifies possible substitute fuels for motor carriers and railroads that are currently available and under development. It identifies which of these substitutes are likely to be used in the near and medium term years and the circumstances under which they will be used. The paper discusses which fuel efficiency measures have been successfully adopted by railroads and motor carriers. Finally, it suggests opportunities for transportation researchers to evaluate investment options to improve fuel efficiencies in freight transportation

A rolling horizon approach for the locomotive routing problem at the Canadian National Railway Company

Cette thèse étudie le problème du routage des locomotives qui se pose à la Compagnie des chemins de fer nationaux du Canada (CN) - le plus grand chemin de fer au Canada en termes de revenus et de taille physique de son réseau ferroviaire. Le problème vise à déterminer la séquence des activités de chaque locomotive sur un horizon de planification donné. Dans ce contexte, il faut prendre des décisions liées à l'affectation de locomotives aux trains planifiés en tenant compte des besoins d'entretien des locomotives. D’autres décisions traitant l'envoi de locomotives aux gares par mouvements à vide, les déplacements légers (sans tirer des wagons) et la location de locomotives tierces doivent également être prises en compte. Sur la base d'une formulation de programmation en nombres entiers et d'un réseau espace-temps présentés dans la littérature, nous introduisons une approche par horizon roulant pour trouver des solutions sous-optimales de ce problème dans un temps de calcul acceptable. Une formulation mathématique et un réseau espace-temps issus de la littérature sont adaptés à notre problème. Nous introduisons un nouveau type d'arcs pour le réseau et de nouvelles contraintes pour le modèle pour faire face aux problèmes qui se posent lors de la division de l'horizon de planification en plus petits morceaux. Les expériences numériques sur des instances réelles montrent les avantages et les inconvénients de notre algorithme par rapport à une approche exacte.This thesis addresses the locomotive routing problem arising at the Canadian National Railway Company (CN) - the largest railway in Canada in terms of both revenue and the physical size of its rail network. The problem aims to determine the sequence of activities for each locomotive over the planning horizon. Besides assigning locomotives to scheduled trains and considering scheduled locomotive maintenance requirements, the problem also includes other decisions, such as sending locomotives to stations by deadheading, light traveling, and leasing of third-party locomotives. Based on an Integer Programming formulation and a Time-Expanded Network presented in the literature, we introduce a Rolling Horizon Approach (RHA) as a method to find near-optimal solutions of this problem in acceptable computing time. We adapt a mathematical formulation and a space-time network from the literature. We introduce a new type of arcs for the network and new constraints for the model to cope with issues arising when dividing the planning horizon into smaller ones. Computational experiments on real-life instances show the pros and cons of our algorithm when compared to an exact solution approach

Locomotive assignment problem with heterogeneous vehicle fleet and hiring external locomotives

This paper focuses on solving the problem of how to assign locomotives to assembled trains optimally. To solve the problem, linear programming is applied. The situation we model in the paper occurs in the conditions of a transport operator that provides rail transport in the Czech Republic. In the paper, an extended locomotive assignment problem is modeled; the transport operator can use different classes of the locomotives to serve individual connections, some connections must be served by a predefined locomotive class, and the locomotives can be allocated to several depots at the beginning. The proposed model also takes into consideration the fact that some connections can be served by the locomotives of external transport companies or operators. The presented model is applied to a real example in order to test its functionality.Web of Science2015art. no. 58390

Optimizing Fueling Decisions for Locomotives in Railroad Networks

Even though rail transportation is one of the most fuel efficient forms of surface transportation, fueling costs are one of the highest operating cost head for railroad companies. In US, unlike Europe, fueling costs are indeed, by far, the single highest operating cost. For larger companies with several thousands of miles of rail network, the fuel bills often run into several billions of dollars annually. The railroad fueling problem considered in this paper has three distinct cost components. Fueling stations charge a location dependent price for the fuel in addition to a fixed contracting fee over the entire planning horizon. In addition, the railroad company must also bear incidental and notional costs for each fuelling stop. It is imperative that the number of fueling stops between an origin and destination should be restricted to avoid unnecessary delays. This paper proposes a mixed integer linear program model that determines the optimal strategy for contracting and fuel purchase schedule decisions that minimizes overall costs under certain reasonable assumptions. This model is tested on a large, real-life problem instances. This mathematical model is further enhanced by introducing several feasible MIP cuts. This paper compares the efficiency of different MIP cuts in order to reduce the run-time. Lastly, the paper concludes with an observation that even though the problem scale was expected to diminish the model performance, it was indeed noted that run-time and memory requirements are fairly reasonable. It thus establishes that this problem must be looked beyond the prism of heuristics and other approximate algorithms for actual implementation at railroad companies

Developing a Sustainable Freight Transportation Framework with the Consideration of Improving Safety and Minimizing Carbon Emissions

Despite the difficulties of the American economy in recent years the transportation sector continues to expand. Freight transportation alone has been projected to increase enormously even if the economy as a whole only manages a very moderate growth. Not only does freight transportation use a large percentage of resources but it contributes significantly to America’s share of carbon emissions and affects the safety of the transportation system and all its users. These problems are only expected to increase as the volume of freight transportation is already reaching the limit of the American transportation infrastructure’s capacity and demand continues to increase. The primary objective of this research was to compile a list of technologies and practices that should be included in the sustainable freight transportation frameworks of government agencies and commercial fleets to reduce their carbon footprint and increase their safety by providing recommendations on promising legislation, research, technologies, and practices. Data was gathered through a literature review of available materials and a survey of the state Departments of Transportation. The success of this research project provides the needed knowledge for the development of a sustainable freight transportation framework

Should You Buy A Hybrid Car?

The question of whether or not a hybrid car is the right choice for a consumer is one that plagues the modern consumer. The advantages and disadvantages in regards to purchasing a hybrid car were examined. Interviews were conducted with hybrid car dealers, professors, and WPI students. Research was done into the history of hybrid cars and how hybrid cars operate. Hybrid cars turned out to be evenly matched with the non-hybrid counterparts when all the facts were examined. The money saved due to the improved fuel economy is offset by the premium paid for a hybrid vehicle

Integrated optimization and simulation models for the locomotive refueling system configuration problem

Master of ScienceDepartment of Industrial and Manufacturing Systems EngineeringTodd W. EastonJessica L. Heier StammLocomotives in the U.S. use over 3 billion gallons of fuel each year and faster refueling can increase rail network capacity without the infrastructure cost associated with new terminals or tracks. This thesis introduces the locomotive refueling system configuration problem (LRSCP), which seeks to improve efficiency in refueling yards through new technologies or policies. This research also creates two new methods to solve LRSCP. The first method uses an integer program to solve the off-line LRSCP and develop a static refueling policy. The train refueling integer program, TRIP, maximizes the weighted number of train combinations that can be refueled without delay. TRIP is optimized and its outputs are used as inputs to a simulation developed in Simio® for testing and validation. The second method creates an integrated integer program and simulation to solve the on-line LRSCP and produces a dynamic refueling policy. This tool, built in Python, incorporates a different integer program, the strike line integer program (SLIP), into the simulation. SLIP determines the optimal refueling assignment for each incoming train. The simulation incorporates SLIP’s solution for testing and validation. This tool is truly integrated and requires approximately 300 instances of SLIP to simulate a single day. Based on experimental results, solving either TRIP or SLIP and incorporating the optimal refueling policy improves railyard operations by 10 to 30%. This impact is statistically significant and increases the capacity of a railyard. Additionally, it impacts other important parameters such as time spent in the yard and the maximum queue for the railyard. Furthermore, there is a significant decrease in wasted time and an improvement to railyard efficiency. Implementing either method should increase a railyard’s capacity and significantly increase revenue opportunities