Simulation of operating procedures and infrastructure changes in the upper Mississippi navigation system
Abstract
We use discrete-event simulation to investigate the effects of proposed operational policies and infrastructure changes for a series of locks that create a seasonal bottleneck for commercial barge operations. Traffic scheduling rules derived from a nonlinear integer programming model are tested over highly time-varying traffic mixes and traffic intensities in the shipping season. With the simulation model, we show the impact of alternative priority shifting rules and identify traffic levels at which major infrastructural improvements are required. We identify self-regulating behavior of the system when it is under stress and see how stochastic phenomena mute the benefits of scheduling strategies inferred from deterministic optimizing models. Finally, we compare the benefits derived from infrastructure investments with highly different capital costs. The results are relevant to other transportation or service systems involving series of separated servers with bi-directional traffic flows, several classes of user or customer, random itineraries, and random transit time between servers.
References
[1]
Branke, J. and Mattfeld, D.C. (2005). Anticipation and Flexibility in Dynamic Scheduling. International Journal of Production Research. 45(15) 3103--3129.
[2]
Campbell, J. F., Smith, L. D., Sweeney D. C. II, Mundy, R., Nauss, R. (2007). Decision Tools for Reducing Congestion at Locks on the Upper Mississippi River. HICSS Proceedings 2007.
[3]
Dai, M. D. M. and Schonfeld, P (1998). Metamodels for Estimating Waterway delays through Series of Queues. Transportation Research Part B, 32 (1), 1--20.
[4]
Nauss, R. M. (2007). Optimal Sequencing in the Presence of Setup Times for Tow/Barge Traffic Through a River Lock. EJOR, 187(3) 1268--1281.
[5]
Ronen, D. R., Nauss, R. M., and Doughty, M. (2003). Upper Mississippi River and Illinois Waterways: How to Reduce Waiting Times of Vessels While Using the Current Infrastructure. Center for Transportation Studies, University of Missouri-St. Louis, 23pp.
[6]
Smith, L. D., Sweeney D. C. II, and Campbell, J. F. (2008). Simulation of Alternative Approaches to Relieving Congestion at Locks in a River Transportation System. Journal of the Operational Research Society, in press.
[7]
Sweeney, D. C. (2004). A Discrete Event Simulation Model of a Congested Segment of the Upper Mississippi River Inland Navigation System, Center for Transportation Studies, UM-St. Louis, and U.S. Army Corps of Engineers.
[8]
Ting, C. J. and Schonfeld P. (2001). Control Alternatives at a Waterway Lock. Journal of Waterway, Port, Coastal and Ocean Engineering, ASCE, March/April, 89--96.
[9]
Zhu, L, Schonfeld, P., Kim, Y. M. Flood, I. and Ting C. J. (1999). Queuing Network Analysis for Waterways with Artificial Neural Networks. Artificial Intelligence for Engineering Design, Analysis and Manufacturing, 365--375.
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San Diego, CA, United States
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Published: 14 April 2008
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