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On duality for square root convex programs

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  • C. Scott
  • T. Jefferson

Abstract

Conjugate function theory is used to develop dual programs for nonseparable convex programs involving the square root function. This function arises naturally in finance when one measures the risk of a portfolio by its variance–covariance matrix, in stochastic programming under chance constraints and in location theory. Copyright Springer-Verlag 2007

Suggested Citation

  • C. Scott & T. Jefferson, 2007. "On duality for square root convex programs," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 65(1), pages 75-84, February.
    • Handle: RePEc:spr:mathme:v:65:y:2007:i:1:p:75-84
    DOI: 10.1007/s00186-006-0101-5
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    References listed on IDEAS

    as
    1. Elmor L. Peterson, 1976. "Fenchel's Duality Thereom in Generalized Geometric Programming," Discussion Papers 252, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
    2. Elmor L. Peterson, 1976. "Optimality Conditions in Generalized Geometric Programming," Discussion Papers 221, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
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