Modeling a Coal Car Cooperative Transportation Network – UA09-AECC

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Modeling a Coal Car Cooperative Transportation Network – UA09-AECC

This project addresses transportation problems with the development of a Decision Support Tool (in Microsoft Excel® using Visual Basic for Applications® (VBA)) that allows the user to analyze different scenarios of this process.


Arkansas Electric Cooperative

Research Team:

Sarah Root, Hector Vergara, Chase E. Rainwater

Universities Involved:

University of Arkansas

Start Date:


End Date:



The goal of this project was to develop a descriptive model of Arkansas Electric Cooperative Corporation’s (AECC) transportation network. This model takes as input a given transportation scenario and evaluates the performance of that scenario with respect to many performance metrics (e.g., cost, coal throughput, etc.). In addition, the project implemented this model using Visual Basic for Applications so that many scenarios could be easily considered and analyzed.
AECC and the Center for Excellence in Logistics and Distribution (CELDi) model AECC transportation network. In addition to being able to represent their current transportation strategy, the model developed by the CELDi research team would also be used to evaluate different transportation and distribution strategies. This would allow the CELDi research team to use the model as a means to identify potential improvements in the AECC transportation network. These improvements could take many forms such as operational changes, infrastructure improvements or rolling stock improvements, for example, among many others. The CELDi research team will consist of two faculty members – Drs. Sarah Root and Chase Rainwater – and one industrial engineering graduate student.
Some reasonable scenarios for a CCC that have been tested in our study exhibit promise. They generally seem to be volume feasible. These results motivate pursuing a more detailed analysis of this concept. However, the results for test instances are highly dependent on the participants that are included in the scenario and their roles in the CCC. For this reason, it is difficult to recognize a threshold behavior in terms volume or benefits for a range of plants. The flexibility of the decision support tool allows the analyst to consider many scenarios. This will certainly help AECC to evaluate different alternative CCC scenarios when approaching other utilities that would want to participate and also negotiating with the Class I Railroads.