Skip to main content

Advertisement

SpringerLink
Log in

Solving a bi-objective winner determination problem in a transportation procurement auction

  • Original Paper
  • Published:
Logistics Research

Abstract

This paper introduces a bi-objective winner determination problem which arises in the procurement of transportation contracts via combinatorial auctions where bundle bidding is possible. The problem is modelled as a bi-objective extension to the set covering problem. We consider both the minimisation of the total procurement costs and the maximisation of the service-quality level at which the transportation contracts are executed. Taking into account the size of real-world transport auctions, a solution method has to cope with problems of up to some hundred contracts and a few thousand bundle bids. To solve the problem, we propose a bi-objective branch-and-bound algorithm and eight variants of a multiobjective genetic algorithm. Artificial benchmark instances that comply with important economic features of the transport domain are introduced to evaluate the methods. The branch-and-bound approach is able to find the optimal trade-off solutions in reasonable time for very small instances only. The eight variants of the genetic algorithm are compared among each other by means of large instances. The best variant is also evaluated using the small instances with known optimal solutions. The results indicate that the performance largely depends on the initialisation heuristic and suggest also that a well-balanced combination of genetic operators is crucial to obtain good solutions.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  1. Abrache J, Crainic T, Rekik MGM (2007) Combinatorial auctions. Ann Oper Res 153(34):131–164

    Article  MathSciNet  Google Scholar 

  2. Buer T, Pankratz G (2008) Ein pareto-optimierungsverfahren für ein mehrkriterielles gewinnerermittlungsproblem in einer kombinatorischen transportausschreibung. In: Bortfeldt A, Homberger J, Kopfer H, Pankratz G, Strangmeier R (eds) Intelligente Entscheidungsunterstützung. Gabler Verlag, Wiesbaden, pp 113–135

    Google Scholar 

  3. Caplice C, Sheffi Y (2003) Optimization-based procurement for transportation services. J Business Logist 24(2):109–128

    Article  Google Scholar 

  4. Caplice C, Sheffi Y (2006) Combinatorial auctions for truckload transportation. In: Cramton P, Shoaham Y, Steinberg R (eds) (2006) MIT Press, Cambridge, pp 539–571

  5. Cargoclix Dr. Meier & Schmidt GmbH (2010) Success stories. http://www.cargoclix.com/info/en/success-stories/page.html. Last accessed 22 March 2010

  6. Chankong V, Haimes YY (1983) Multiobjective decision making: theory and methodology. Wiley, New York

    Google Scholar 

  7. Cramton P, Shoaham Y, Steinberg R (eds) (2006) Combinatorial auctions, MIT Press, Cambridge, MA

  8. Ehrgott M, Fonseca CM, Gandibleux X, Hao JK, Sevaux M (eds) (2009) Evolutionary multi-criterion optimization, fifth international conference, EMO 2009, Nantes, April 2009, Proceedings, Lecture notes in computer science, vol 5467. Springer

  9. Eiben A, Smith J (2003) Introduction to evolutionary computing. Springer, Berlin

    Book  Google Scholar 

  10. Elmaghraby W, Keskinocak P (2004) Combinatorial auctions in procurement. In: Harrison T, Lee H, Neale J (eds) The practice of supply chain management: where theory and application converge. Springer, New York, pp 245–258

    Google Scholar 

  11. ETH Zurich (2009) ETH Zurich, System optimization, Pisa. ETH Zurich, System Optimization. http://www.tik.ee.ethz.ch/sop/pisa/. Last accessed 30 January 2009

  12. Feo T, Resende M (2005) Greedy randomized adaptive search procedures. J Glob Optim 6:109–133

    Article  MathSciNet  Google Scholar 

  13. Haimes Y, Lasdon L, Wismer D (1971) On a bicriterion formulation of the problems of integrated system identification and system optimization. IEEE Trans Syst Man Cybern 1(3):296–297

    Article  MathSciNet  Google Scholar 

  14. Hudson B, Sandholm T (2004) Effectiveness of query types and policies for preference elicitation in combinatorial auctions. In: 3rd international joint conference on Autonomous Agents and Multiagent Systems (AAMAS 2004), IEEE Computer Society, Washington, pp 386–393

  15. Ledyard JO, Olson M, Porter D, Swanson JA, Torma DP (2002) The first use of a combined value auction for transportation services. Interfaces 32:4–12

    Google Scholar 

  16. Leyton-Brown K, Shoham Y (2006) A test suite for combinatorial auctions. In: Cramton P, Shoaham Y, Steinberg R (eds) Combinatorial auctions, MIT Press, Cambridge, pp 451–478

  17. Meisell MJ, Norbis M (2008) A review of the transportation mode choice and carrier selection literature. Int J Logist Manag 19(2):183–2111

    Article  Google Scholar 

  18. Nisan N (2000) Bidding and allocation in combinatorial auctions. In: EC ’00: Proceedings of the 2nd ACM conference on Electronic commerce, pp 1–12

  19. Sandholm T, Suri S, Gilpin A, Levine D (2002) Winner determination in combinatorial auctions generalizations. In: International conference on Autonomous Agents and Multi-Agent Systems (AAMAS), Bologna, pp 69–76

  20. Sheffi Y (2004) Combinatorial auctions in the procurement of transportation services. Interfaces 34(4):245–252

    Article  Google Scholar 

  21. Song J, Regan A (2004) Combinatorial auctions for transportation service procurement: the carrier perspective. Transp Res Record 1833:40–46

    Google Scholar 

  22. Suhl L, Mellouli T (2009) Optimierungssysteme—Modelle, Verfahren, Software, Anwendungen. Springer, Berlin

    Google Scholar 

  23. Zitzler E, Thiele L (1999) Multiobjective evolutionary algorithms: a comparative case study and the strength pareto approach. IEEE Trans Evol Comput 3(4):257–271

    Article  Google Scholar 

  24. Zitzler E, Laumanns M, Thiele L (2002) Spea2: improving the strength pareto evolutionary algorithm for multiobjective optimization. In: Giannakoglou K, Tsahalis D, Periaux J, Papailiou K, Fogarty T (eds) Proceedings of the EUROGEN2001 conference, CIMNE, Barcelona, pp 95–100

  25. Zitzler E, Thiele L, Laumanns M, Fonseca CM, da Fonseca VG (2003) Performance assessment of multiobjective optimizers: An analysis and review. IEEE Trans Evol Comput 7:117–132

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Information Systems, Faculty of Business Administration and Economics, University of Hagen, 58084, Hagen, Germany

    Tobias Buer & Giselher Pankratz

Authors
  1. Tobias Buer
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Giselher Pankratz
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Tobias Buer.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Buer, T., Pankratz, G. Solving a bi-objective winner determination problem in a transportation procurement auction. Logist. Res. 2, 65–78 (2010). https://doi.org/10.1007/s12159-010-0031-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12159-010-0031-8

Keywords

Search

Navigation