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A stochastic programming winner determination model for truckload procurement under shipment uncertainty

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  • Ma, Zhong
  • Kwon, Roy H.
  • Lee, Chi-Guhn

Abstract

We propose a two-stage stochastic integer programming model for the winner determination problem (WDP) in combinatorial auctions to hedge the shipper's risk under shipment uncertainty. The shipper allows bids on combinations of lanes and solves the WDP to determine which carriers are to be awarded lanes. In addition, many other important comprehensive business side constraints are included in the model. We demonstrate the value of the stochastic solution over one obtained by a deterministic model based on using average shipment volumes. Computational results are given that indicate that moderately sized realistic instances can be solved by commercial branch and bound solvers in reasonable time.

Suggested Citation

  • Ma, Zhong & Kwon, Roy H. & Lee, Chi-Guhn, 2010. "A stochastic programming winner determination model for truckload procurement under shipment uncertainty," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 46(1), pages 49-60, January.
  • Handle: RePEc:eee:transe:v:46:y:2010:i:1:p:49-60
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    Citations

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    Cited by:

    1. Feki, Yassin & Hajji, Adnène & Rekik, Monia, 2016. "A hedging policy for carriers’ selection under availability and demand uncertainty," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 85(C), pages 149-165.
    2. Jothi Basu, R. & Bai, Ruibin & Palaniappan, PL.K., 2015. "A strategic approach to improve sustainability in transportation service procurement," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 74(C), pages 152-168.
    3. Rancourt, Marie-Ève & Bellavance, François & Goentzel, Jarrod, 2014. "Market analysis and transportation procurement for food aid in Ethiopia," Socio-Economic Planning Sciences, Elsevier, vol. 48(3), pages 198-219.
    4. Xu, Su Xiu & Huang, George Q., 2013. "Transportation service procurement in periodic sealed double auctions with stochastic demand and supply," Transportation Research Part B: Methodological, Elsevier, vol. 56(C), pages 136-160.
    5. Mesa-Arango, Rodrigo & Ukkusuri, Satish V., 2013. "Benefits of in-vehicle consolidation in less than truckload freight transportation operations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 60(C), pages 113-125.
    6. Xu, Su Xiu & Huang, George Q., 2014. "Efficient auctions for distributed transportation procurement," Transportation Research Part B: Methodological, Elsevier, vol. 65(C), pages 47-64.
    7. Bo Zhang & Hongwei Ding & Hongbo Li & Wei Wang & Tao Yao, 2014. "A Sampling-Based Stochastic Winner Determination Model for Truckload Service Procurement," Networks and Spatial Economics, Springer, vol. 14(2), pages 159-181, June.
    8. Xu, Su Xiu & Cheng, Meng & Huang, George Q., 2015. "Efficient intermodal transportation auctions for B2B e-commerce logistics with transaction costs," Transportation Research Part B: Methodological, Elsevier, vol. 80(C), pages 322-337.
    9. Zhang, Bo & Yao, Tao & Friesz, Terry L. & Sun, Yuqi, 2015. "A tractable two-stage robust winner determination model for truckload service procurement via combinatorial auctions," Transportation Research Part B: Methodological, Elsevier, vol. 78(C), pages 16-31.
    10. Mesa-Arango, Rodrigo & Ukkusuri, Satish V., 2015. "Demand clustering in freight logistics networks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 81(C), pages 36-51.

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