Waterway maintenance budget allocation in a multimodal network

Abstract The U.S. inland waterway system has more than 11,000 miles of maintained navigation channel, which carries a significant percentage of the national freight total. Maintenance operations, including dredging and lock and dam maintenance/repair, are important to ensuring the effective and efficient operation of the inland marine transportation system. This study specifically deals with maintenance fund allocation to these projects. It proposes a multimodal approach to formulate the waterway maintenance problem in a network that considers rivers, locks/dams, highways and railways. The random effects of channel infilling known as shoaling are also considered. Maintenance on locks and dams reduces the delay therein, the cost of which is also considered in the model. The solution identifies maintenance projects to fund with an objective to serve the OD demand and minimize the total shipping costs on the network. The model is tested using data from the Ohio River Basin network. The proposed model is effective, and the result indicates a trade-off between lock/dam maintenance versus channel dredging. A distinct feature of this study is its explicit modeling of the interdependency between projects in realizing the system benefits as well as the random shoaling effect.

[1]  P R Murphy,et al.  THE RELATIVE IMPORTANCE OF COST AND SERVICE IN FREIGHT TRANSPORTATION CHOICE BEFORE AND AFTER DEREGULATION: AN UPDATE , 1995 .

[2]  F Southworth,et al.  Economic Foundations of Ohio River Navigation Investment Model , 2004 .

[3]  Kelly M. Sullivan,et al.  Budgeting maintenance dredging projects under uncertainty to improve the inland waterway network performance , 2018, Transportation Research Part E: Logistics and Transportation Review.

[4]  Jay R. Lund.  Scheduling Maintenance Dredging on Single Reach with Uncertainty , 1990 .

[5]  Mohammadadel Khodakarami,et al.  Modeling Maintenance Project Selection on a Multimodal Transportation Network , 2014 .

[6]  Samuel J. Ratick,et al.  Risk-Based Spatial Decision Support System for Maintenance Dredging of Navigation Channels , 1996 .

[7]  Mohammadadel Khodakarami.  Waterway System Maintenance Optimization , 2016 .

[8]  Kenneth Ned Mitchell,et al.  Underkeel Clearance Reliability Model for Dredged Navigation Channels , 2017 .

[10]  David Grier,et al.  Harbor maintenance trust fund , 2005 .

[11]  Paul Schonfeld,et al.  Scheduling Interdependent Waterway Projects Through Simulation and Genetic Optimization , 2005 .

[12]  Kelly M. Sullivan,et al.  Efficient Dredging Strategies for Improving Transportation Infrastructure Resilience: August 1, 2014 – December 31, 2016: Final Research Report , 2017 .

[13]  William W. Wilson,et al.  Impacts of Lock Capacity Expansion on Delay Costs for Grain Shipped on the Mississippi River , 2011 .

[14]  L. A. Baranov,et al.  Reliability of systems with periodic piecewise constant failure rate , 2017 .

[15]  Kenneth Ned Mitchell,et al.  Improved Waterway Network Maintenance Strategies via Genetic Algorithms , 2015 .

[16]  David T. Ford.  Dredged‐Material Disposal System Capacity Expansion , 1986 .

[17]  David T. Ford,et al.  Dredged‐Material Disposal Management Model , 1984 .

[18]  Bruce X Wang,et al.  Selection of Dredging Projects for Maximizing Waterway System Performance , 2013 .

[19]  Yuri A Ermolin.  Reliability calculation under seasonally varying failure rate. , 2007, ISA transactions.

[20]  Wesley W. Wilson,et al.  A Description of the Inland Waterway Systems and Planning Models , 2007 .