Skip to main content
Log in

“Cap and Trade” for Congestion Control

  • Published:
Dynamic Games and Applications Aims and scope Submit manuscript

Abstract

We study a “cap and trade” scheme for congestion control: the planner sets constraints for aggregate utilization on certain critical links in a given network and competitive trading of usage rights in a secondary market is expected to identify over time prices clearing demand for the utilization of the constrained links. If prices in a “cap and trade” scheme stabilize relatively quickly, a social planner can fine-tune the caps for aggregate utilization on critical links. However, it is not clear that prices would necessarily stabilize as users dynamically adjust their route and/or flow choices. In this paper we show that prices and flows (or routes) do stabilize in a “cap and trade” scheme for congestion control when users are assumed to adjust their flow (or route) choices by optimizing vis-à-vis current conditions. A sufficient condition for this result pertains to the relative speed of trading versus users’ adjustments. We find that prices stabilize and flows (or routes) converge to an equilibrium if the pace at which prices are updated is faster than that at which users adjust their decisions.

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

Access this article

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

Instant access to the full article PDF.

Fig. 1

Similar content being viewed by others

References

  1. Altman E, Boulogne T, El-Azouzi R, Jimenez T, Wynter L (2006) A survey on networking games in telecommunications. Comput Oper Res 33(2):286–311

    Article  MathSciNet  MATH  Google Scholar 

  2. Arrow K, Hurwicz L (1958) On the stability of competitive equilibrium I. Econometrica 26:522–552

    Article  MathSciNet  MATH  Google Scholar 

  3. Bala V, Majumdar M (1992) Chaotic tatonnement. Econ Theory 2:437–445

    Article  MathSciNet  MATH  Google Scholar 

  4. Beckman M, McGuire C, Winsten C (1956) Studies in the economics of transportation. Yale University Press, New Haven

    Google Scholar 

  5. Cominetti R, Melo E, Sorin S (2010) A payoff-based learning procedure and its application to traffic games. Games Econ Behav 70:71–83

    Article  MathSciNet  MATH  Google Scholar 

  6. Haurie A, Marcotte P (1985) On the relationship between Nash-Cournot and Wardrop equilibria. Networks 15(3):295–308

    Article  MathSciNet  MATH  Google Scholar 

  7. Larsson T, Patriksson M (1995) An augmented Lagrangean dual algorithm for link capacity side constrained traffic assignment problems. Transp Res, Part B, Methodol 29:433–455

    Article  Google Scholar 

  8. Larsson T, Patriksson M (1999) Side constrained traffic equilibrium models: analysis, computation and applications. Transp Res, Part B, Methodol 33:233–264

    Article  Google Scholar 

  9. Larsson T, Patriksson M, Stromberg A (1999) Ergodic, primal convergence in dual subgradient schemes for convex programming. Math Program 86:283–312

    Article  MathSciNet  MATH  Google Scholar 

  10. Montgomery D (1972) Markets in licenses and efficient pollution control programs. J Econ Theory 5(3):395–418

    Article  Google Scholar 

  11. Nikaido H, Uzawa H (1960) Stability and non-negativity in a Walrasian process. Int Econ Rev 1:5–59

    Article  Google Scholar 

  12. Patriksson M (1994) Traffic assignment problems: models and methods. Topics in transportation series. VSP, Utrecht

    Google Scholar 

  13. Pigou AC (1920) The economics of welfare. Macmillan, London

    Google Scholar 

  14. Saari DG (1985) Iterative price mechanisms. Econometrica 53:1117–1131

    Article  MathSciNet  MATH  Google Scholar 

  15. Sandholm W (2002) Evolutionary implementation and congestion pricing. Rev Econ Stud 69:667–689

    Article  MathSciNet  MATH  Google Scholar 

  16. Sandholm W (2005) Negative externalities and evolutionary implementation. Rev Econ Stud 72:885–915

    Article  MathSciNet  MATH  Google Scholar 

  17. Uzawa H (1958) Iterative methods for concave programming. In: Arrow K, Hurwicz L, Uzawa H (eds) Studies in linear and non-linear programming. Stanford University Press, Stanford, pp 154–165

    Google Scholar 

  18. Vickrey W (1969) Congestion theory and transport investment. Am Econ Rev 59:251–260

    Google Scholar 

  19. Wardrop JG (1952) Some theoretical aspects of road traffic research. In: Proceedings of the institute of civil engineers, part II, pp 325–378

    Google Scholar 

  20. Weitzman M (1974) Prices vs quantities. Rev Econ Stud 41(4):477–491

    Article  Google Scholar 

Download references

Acknowledgements

This work was partially supported by AFOSR (Air Force Office of Scientific Research) through grant FA9550-09-1-0368.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Alfredo Garcia.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Garcia, A., Hong, M. & Barrera, J. “Cap and Trade” for Congestion Control. Dyn Games Appl 2, 280–293 (2012). https://doi.org/10.1007/s13235-012-0049-4

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13235-012-0049-4

Keywords

Navigation