Pricing and Segmentation of Stochastic Demand in Truckload Combinatorial Bids

A bidding advisory model for truckload combinatorial auctions with stochastic demand (BMoTS) is proposed hereby. The contributions of this work are: (1) using value-based pricing for bidding rules, (2) segmenting the maximum volume of demand that a carrier is willing to serve, and (3) incorporating demand uncertainty. The algorithm efficiently solves stochastic minimum-cost flow problems and constructs bids that combine synergetic lanes in profitable tours. A numerical experiment illustrates the application of BMoTS.

• Supplemental Notes:
  • This paper was sponsored by TRB committee AT015 Standing Committee on Freight Transportation Planning and Logistics.
• Corporate Authors:

  Transportation Research Board

  500 Fifth Street, NW
  Washington, DC  United States  20001
• Authors:
  • Mesa-Arango, Rodrigo
  • Ukkusuri, Satish V
• Conference:
  • Transportation Research Board 95th Annual Meeting
  • Location: Washington DC, United States
  • Date: 2016-1-10 to 2016-1-14
• Date: 2016

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; References; Tables;
• Pagination: 20p
• Monograph Title: TRB 95th Annual Meeting Compendium of Papers

Subject/Index Terms

• TRT Terms: Algorithms; Competitive bidding; Demand; Freight service; Logistics; Pricing; Stochastic programming; Trucking
• Subject Areas: Finance; Freight Transportation; Planning and Forecasting; I10: Economics and Administration; I72: Traffic and Transport Planning;

Filing Info

• Accession Number: 01590736
• Record Type: Publication
• Report/Paper Numbers: 16-2100
• Files: TRIS, TRB, ATRI
• Created Date: Feb 22 2016 1:18PM