THESIS DEFENSE :: Procurement in Truckload Transportation

Event Details
  • Date/Time:
    • Wednesday December 13, 2006 - Tuesday December 12, 2006
      12:30 pm - 11:00 pm
  • Location: 226A Groseclose Building
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    N/A
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Contact
Barbara Christopher
Industrial and Systems Engineering
Contact Barbara Christopher
404.385.3102
Summaries

Summary Sentence: THESIS DEFENSE :: Procurement in Truckload Transportation

Full Summary: THESIS DEFENSE :: Procurement in Truckload Transportation

In this thesis, we address a number of operational challenges encountered in two emerging types of practices in the procurement of truckload transportation services: collaboration and auctions. The main objective in these two types of procurement strategies is identifying and exploiting synergies between the lanes of a carrier's network. In shipper collaboration, we take the perspective of a shipper who collaborates with other shippers to seek synergy between his lanes and other participants' lanes. On the other hand, in procurement auctions, although we take the carriers' perspective in our work, a shipper tries to discover the carrier (or carriers) whose network has the most synergy with his lanes.

The first part of the thesis concerns the solution of optimization problems arising in collaborative transportation procurement networks where a group of shippers come together and jointly negotiate with carriers for the procurement of transportation services. In the highly fragmented truckload transportation industry a substantial fraction of truck movements involves empty trucks, i.e., involves moves that reposition trucks. However, reducing the amount of truck repositioning is difficult because the need for a carrier to reposition its trucks depends on the interactions between the shippers the carrier is serving. Through collaboration, shippers may be able to identify and submit sequences of continuous loaded movements to carriers, reducing the carriers' need for repositioning, and thus lowering the carriers' costs. A portion of the carriers' cost savings may be returned to the shippers in the form of lower prices. We discuss optimization technology that can be used to assist in the identification of repeatable, dedicated truckload continuous move tours with little truck repositioning. Timing considerations are critical to practical viability and are a key focus of our efforts. We demonstrate the effectiveness of the algorithms developed on various randomly generated instances as well as on instances derived from data obtained from a strategic sourcing consortium for a $14 billion dollar sized US industry.

The second part of the thesis concerns the pricing of transportation services offered by the trucking companies (carriers). We look at the bid determination problem faced by carriers in transportation procurement auctions where a shipper requests quotes from the carriers and purchases the services of the lowest bidder. Determining the optimal bid values for a carrier poses several challenging research questions. The specific problem being studied is the bid valuation problem in the case where the carrier must place bids on multiple lanes simultaneously. For each lane, the carrier's bid must be high enough to make it profitable for the carrier but low enough to give the carrier a good chance of winning that lane. The difficulty is that the operating cost of the carrier depends on the set of lanes the carrier wins which is not known until the end of the auction. We model the problem as a stochastic optimization problem and propose a coordinate search algorithm for solving this problem. Then, we conduct a simulation study to demonstrate the positive impact of the approach on carrier profits.

In both problems considered in the thesis, the central issue is identifying and exploiting synergies between the lanes of a carrier's network.

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H. Milton Stewart School of Industrial and Systems Engineering (ISYE)

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Status
  • Created By: Barbara Christopher
  • Workflow Status: Published
  • Created On: Oct 8, 2010 - 7:32am
  • Last Updated: Oct 7, 2016 - 9:52pm