IDEAS home Printed from https://ideas.repec.org/a/kap/compec/v13y1999i2p103-15.html
   My bibliography  Save this article

Solving Irregular Econometric and Mathematical Optimization Problems with a Genetic Hybrid Algorithm

Author

Listed:
  • Ostermark, Ralf

Abstract

In the present paper we apply a new Genetic Hybrid Algorithm (GHA) to globally minimize a representative set of ill-conditioned econometric/mathematical functions. The genetic algorithm was specifically designed for nonconvex mixed integer nonlinear programming problems and it can be successfully applied to both global and constrained optimization. In previous studies, we have demonstrated the efficiency of the GHA in solving complicated NLP, INLP and MINLP problems. The present study is a continuation of this research, now focusing on a set of highly irregular optimization problems. In this paper we discuss the genetic hybrid algorithm, the nonlinear problems to be solved and present the results of the empirical tests. Citation Copyright 1999 by Kluwer Academic Publishers.

Suggested Citation

  • Ostermark, Ralf, 1999. "Solving Irregular Econometric and Mathematical Optimization Problems with a Genetic Hybrid Algorithm," Computational Economics, Springer;Society for Computational Economics, vol. 13(2), pages 103-115, April.
  • Handle: RePEc:kap:compec:v:13:y:1999:i:2:p:103-15
    as

    Download full text from publisher

    File URL: http://journals.kluweronline.com/issn/0927-7099/contents
    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

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


    Cited by:

    1. Kapetanios, George, 2007. "Variable selection in regression models using nonstandard optimisation of information criteria," Computational Statistics & Data Analysis, Elsevier, vol. 52(1), pages 4-15, September.
    2. Kapetanios, George, 2006. "Cluster analysis of panel data sets using non-standard optimisation of information criteria," Journal of Economic Dynamics and Control, Elsevier, vol. 30(8), pages 1389-1408, August.
    3. Ostermark, Ralf, 2001. "Genetic modelling of multivariate EGARCHX-processes: evidence on the international asset return signal response mechanism," Computational Statistics & Data Analysis, Elsevier, vol. 38(1), pages 71-93, November.
    4. Ostermark, Ralf, 2004. "A multipurpose parallel genetic hybrid algorithm for non-linear non-convex programming problems," European Journal of Operational Research, Elsevier, vol. 152(1), pages 195-214, January.
    5. Trindade, Graça & Ambrósio, Jorge, 2012. "An optimization method to estimate models with store-level data: A case study," European Journal of Operational Research, Elsevier, vol. 217(3), pages 664-672.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    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:13:y:1999:i:2:p:103-15. See general information about how to correct material in RePEc.

    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 bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.