Toward an Intelligent Brokerage Platform

Abstract

In commercial transportation operations, one of the largest wasteful expenditures is the movement of tractor trailers with little or no cargo. Analysis of interfleet data shows many lost opportunities for identifying backhauling loads—cargo that could have been moved by an otherwise empty trailer on its return from a delivery point to its home base. Brokerage systems that facilitate matching of load-sharing and backhaul opportunities currently do not incorporate monitoring of real-time, geo-based information, analysis of historical geo-based information, and user-calibrated preferences from all brokerage participants. Future intelligent brokerage systems will need to provide a full range of services including supply chain visibility and automated identification of potential collaborations based on historical trends. In this paper an algorithm is described for identifying load-sharing and backhaul opportunities based on the detection of patterns in large-scale, event-based telematics network data.

Get full access to this article

View all access options for this article.

References

American Trucking Association: Economics and Statistics Group. Standard Trucking and Transportation Statistics, Vol. 13, No. 1, 2007.

U.S. Environmental Protection Agency: Office of Transportation and Air Quality. SmartWay EPA. July 17, 2008. www.epa.gov/smartway/.

Demirel

Van Ommeren

and Rietveld

. Matching Model for the Backhaul Problem. Tinbergen Institute Discussion Paper TI 07-083/3. Tinbergen Institute, Amsterdam, Netherlands, 2007.

Felton

The Impact of Rate Regulation Upon ICC-Regulated Truck Back Hauls. Journal of Transport Economics and Policy, Vol. 15, No. 3 1981, pp. 253–267.

Brewer

and Plott

. A Decentralized, Smart Market Solution to a Class of Back-Haul Transportation Problems: Concepts and Experimental Test Beds. INTERFACES, Vol. 32, No. 5 2002, pp. 13–36.

Wang

and Regan

A. C.

. Local Truckload Pickup and Delivery with Hard Time Window Constraints. Transportation Research Part B, Vol. 36, 2002, pp. 78–94.

Potvin

J. Y.

Duhamel

and Guertin

. A Genetic Algorithm for the Vehicle Routing Problem. Computer and Operations Research, Vol. 30, 2003, pp. 787–800.

Chen

Shi

Thomas

Wikum

Jarosinski

Sun

and Gifford

. Data-Mining-Based Decision System Framework for Local Pickup and Delivery Problem. Presented at INFORMS Annual Meeting, Seattle, Wash., 2007.

Ashbrook

and Starner

. Learning Significant Locations and Predicting User Movement with GPS. Proc., 6th International Symposium on Wearable Computers, Seattle, Wash., 2002.

10.

Zhou

Terveen

and Shekhar

. Discovering Personal Paths from Sparse GPS Traces. Proc., JCIS 2005 Workshop on Data Mining, Salt Lake City, Utah, 2005.

11.

Wolf

Guensler

and Bachman

. Elimination of the Travel Diary: An Experiment to Derive Trip Purpose from GPS Travel Data. In Transportation Research Record: Journal of the Transportation Research Board, No. 1768, TRB, National Research Council, Washington, D.C., 2001, pp. 125–134.

12.

Liao

Patterson

Dieter

and Kautz

. Building Personal Maps From GPS Data. Annals of the New York Academy of Sciences, Vol. 1093, 2006, pp. 249–265.

13.

Zhang

Liu

Wang

and Xie

. Learning Transportation Mode from Raw GPS Data for Geographic Applications on the Web. Proc., World Wide Web Conference, Beijing, 2008.

14.

Hudson

and Rhys-Tyle

. Using GPS Data to Calculate the Length and Variability of Freight Vehicle Journey Times on Motorways. Proc., 12th IEE International Conference on Road Transport Information and Control, London, 2004, pp. 49–55.

15.

Ormsby

Napoleon

Burke

Groessl

and Feaster

. Getting to Know ArcGIS Desktop: Basics of ArcView, ArcEditor and ArcInfo. ESRI Press, Redlands, Calif., 2004.

16.

ArcView Network Analyst: An ESRI White Paper. Environmental Systems Research Institute, Inc., Redlands, Calif., 1998.

17.

Song

and Regan

. Approximation Algorithms for the Bid Construction Problem in Combinatorial Auctions for the Procurement of Freight Transportation Contracts. Transportation Research Part B, Vol. 39, No. 10 2005, pp. 914–933.

18.

Wang

and Xia

. 2005. Combinatorial Bid Generation Problem for Transportation Service Procurement. In Transportation Research Record: Journal of the Transportation Research Board, No. 1923, Transportation Research Board of the National Academies, Washington, D.C., 2005, pp. 189–198.

19.

Figliozzi

M. A.

Analysis and Evaluation of Incentive-Compatible Dynamic Mechanisms for Carrier Collaboration. In Transportation Research Record: Journal of the Transportation Research Board, No. 1966, Transportation Research Board of the National Academies, Washington, D.C., 2006, pp. 34–40.