Optimizing Transportation by Inventory Routing and Workload Balancing: Optimizing Daily Dray Operations Across an Intermodal Freight Network

Xiaoqing Sun (), Manish Garg (), Zahir Balaporia (), Kendall Bailey () and Ted Gifford ()
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Xiaoqing Sun: Schneider National Inc., Green Bay, Wisconsin 54306
Manish Garg: Schneider National Inc., Green Bay, Wisconsin 54306
Zahir Balaporia: Schneider National Inc., Green Bay, Wisconsin 54306
Kendall Bailey: Schneider National Inc., Green Bay, Wisconsin 54306
Ted Gifford: Schneider National Inc., Green Bay, Wisconsin 54306

Interfaces, 2014, vol. 44, issue 6, 579-590

Abstract: In rail-based intermodal freight operations, full containers are moved by truck from shipper locations to rail ramps, transported via train to destination ramps, and then moved again by truck to consignee locations. We commonly refer to the roadway portions of this activity as dray operations. In a large metropolitan hub area, such as Chicago or Los Angeles, this drayage activity may involve several hundred drivers and up to 500 daily container moves to or from several distinct rail ramps. Both cost and environmental considerations drive the need to maximize driver productivity and minimize the time and miles not directly associated with moving loaded containers to or from rail ramps. In this paper, we describe a solution to this problem using a set-partitioning formulation and column-generation heuristic and report on a large-scale implementation. We focus on real-world implementation details that include (1) fast solve times to support near-real-time re-solving in the face of constantly changing data, (2) adjustments to account for traffic congestion and other operational considerations, and (3) integration with a commercial transportation management system to provide real-time data to the optimizer and to send solution recommendations to a driver-assignment process.

Keywords: computer science; transportation/shipping; tree algorithms; networks/graphs; deterministic sequencing; production/scheduling; Benders decomposition; algorithms; integer programming; column generation (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (1)

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