Improved Load Plan Design Through Integer Programming Based Local Search

Alan Erera (), Michael Hewitt (), Martin Savelsbergh () and Yang Zhang ()
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Alan Erera: School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332
Michael Hewitt: Department of Industrial and Systems Engineering, Rochester Institute of Technology, Rochester, New York 14623
Martin Savelsbergh: School of Mathematical and Physical Sciences, University of Newcastle, Callaghan, NSW 2308, Australia
Yang Zhang: School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332

Transportation Science, 2013, vol. 47, issue 3, 412-427

Abstract: We present integer programming models of the service network design problem faced by less-than-truckload (LTL) freight transportation carriers and a solution approach for the large-scale instances that result in practical applications. To accurately represent freight consolidation opportunities, the models use a fine discretization of time. Furthermore, the models simultaneously route freight and empty trailers and thus explicitly recognize the efficiencies presented by backhaul lanes. The solution approach can generate the traditional service network designs commonly used by LTL carriers but also enables the construction of designs that allow more flexibility, e.g., that allow freight routes to vary by day of week. An iterative improvement scheme is employed that searches a large neighborhood, each iteration using an integer program. Computational experiments using data from a large U.S. carrier demonstrate that the proposed modeling and solution approach has the potential to generate significant cost savings.

Keywords: network design; freight transportation; heuristic search (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (13)

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Persistent link: https://EconPapers.repec.org/RePEc:inm:ortrsc:v:47:y:2013:i:3:p:412-427

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