Large-Scale, Less-than-Truckload Service Network Design

Ahmad I. Jarrah (), Ellis Johnson () and Lucas C. Neubert ()
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Ahmad I. Jarrah: Department of Decision Sciences, School of Business, The George Washington University, Washington, DC 20052
Ellis Johnson: School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332
Lucas C. Neubert: J. B. Hunt, Lowell, Arkansas 72745

Operations Research, 2009, vol. 57, issue 3, 609-625

Abstract: We present a novel formulation for the service network design problem in the context of large-scale, less-than-truckload (LTL) freight operations. The formulation captures the basic network design constraints; the load-planning requirement that all freight at a location, irrespective of the freight's origin, loads to the same next terminal; and other important LTL-specific requirements. Our modeling scheme fragments the underlying massive network design model with up to 1.3 million 0--1 variables and 1.3 million rows into a separate and efficient integer programming (IP) problem for each destination terminal along with a coordinating master network design problem. We produce high-quality solutions in very reasonable CPU times ((sim)2 hours) using slope scaling and load-planning tree generation with corresponding potential annual savings of $20--25 million dollars for the target company for which the research was conducted.

Keywords: integer programming; transportation; shipping; multicommodity networks (search for similar items in EconPapers)
Date: 2009
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Citations: View citations in EconPapers (29)

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