IDEAS home Printed from
   My bibliography  Save this article

An Introduction to Simulated Annealing Algorithms for the Computation of Economic Equilibrium


  • Wu, Lihua
  • Wang, Yuyun


Economic equilibrium computation has raised the issue of global optimization algorithms since economic equilibrium problems can be cast as a global optimization problem. However, nearly all conventional algorithms stop when they find a local optimum. Over the last decade a number of new optimization algorithms have appeared, simulated annealing is one of them. It is a powerful stochastic search algorithm applicable to a wide range of problems for which little prior knowledge is available, and it asymptotically probabilistically converges to a global optimum. In this paper, we will give a brief introduction to simulated annealing and apply it to the computation of economic equilibrium. We also reported our computational experience in the paper. This early result shows that the application of simulated annealing to computation of economic equilibrium is encouraging and it deserves further research. Citation Copyright 1998 by Kluwer Academic Publishers.

Suggested Citation

  • Wu, Lihua & Wang, Yuyun, 1998. "An Introduction to Simulated Annealing Algorithms for the Computation of Economic Equilibrium," Computational Economics, Springer;Society for Computational Economics, vol. 12(2), pages 151-169, October.
  • Handle: RePEc:kap:compec:v:12:y:1998:i:2:p:151-69

    Download full text from publisher

    File URL:
    Download Restriction: Access to the full text of the articles in this series is restricted.

    As the access to this document is restricted, you may want to search for a different version of it.


    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.

    Cited by:

    1. Paolo Postiglione & M. Andreano & Roberto Benedetti, 2013. "Using Constrained Optimization for the Identification of Convergence Clubs," Computational Economics, Springer;Society for Computational Economics, vol. 42(2), pages 151-174, August.
    2. Creel, Michael & Kristensen, Dennis, 2016. "On selection of statistics for approximate Bayesian computing (or the method of simulated moments)," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 99-114.
    3. Christopher Garcia, 2016. "Winner Determination Algorithms for Combinatorial Auctions with Sub-cardinality Constraints," Computational Economics, Springer;Society for Computational Economics, vol. 47(3), pages 401-421, March.
    4. Roger A. McCain, 2000. "Road Rage: Imitative Learning Of Self-Destructive Behavior In An Agent-Based Simulation," Computing in Economics and Finance 2000 270, Society for Computational Economics.
    5. Grohall, Guenther & Jung, Juergen, 2003. "Multiple Objective Step Function Maximization with Genetic Algorithms and Simulated Annealing," Economics Series 141, Institute for Advanced Studies.

    More about this item


    Access and download statistics


    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:kap:compec:v:12:y:1998:i:2:p:151-69. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Sonal Shukla) or (Rebekah McClure). General contact details of provider: .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.