Tri-Vizor Uses an Efficient Algorithm to Identify Collaborative Shipping Opportunities

Stefan Creemers (), Gert Woumans (), Robert Boute () and Jeroen Beliën ()
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Stefan Creemers: IÉSEG School of Management, 59000 Lille, France; and Research Center for Operations Management, KU Leuven, 3000 Leuven, Belgium
Gert Woumans: IÉSEG School of Management, 59000 Lille, France; and Research Center for Operations Management, KU Leuven, 3000 Leuven, Belgium
Robert Boute: Technology and Operations Management Area, Vlerick Business School, 9000 Ghent, Belgium; and Research Center for Operations Management, KU Leuven, 3000 Leuven, Belgium
Jeroen Beliën: Research Center for Information Management, Modelling and Simulation, KU Leuven, 1000 Brussels, Belgium

Interfaces, 2017, vol. 47, issue 3, 244-259

Abstract: Collaborative shipping programs, whereby companies bundle their transport loads, are a growing trend in logistics. By bundling shipments with other partners, available space in truck hauls for one company can be used to transport shipments for other companies. The benefits are reduced logistics costs and a lower carbon footprint. Although the advantages of collaborative shipping are clear, finding suitable collaboration partners is a major impediment. In this article we present a tool that enables the quick identification of potential partners based on their geographical compatibility, even when the database of shipment lanes is very large. The tool allows the detection of bundling, back-hauling, and round-trip opportunities, as well as “collect-and-or-drop” opportunities in which shipments are collected and (or) dropped off en route. Tri-Vizor, a facilitator and orchestrator of horizontal logistics partnerships, is currently using this tool. Any company that is looking for collaborative shipping partners would also find it valuable. For Tri-Vizor, whose database has grown to over 130,000 shipment lanes, this tool has become an indispensable asset in detecting collaborative shipping opportunities.

Keywords: transport: general; collaborative shipping; optimization (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (11)

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