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Optimality Conditions

  • Wilhelm Forst
  • Dieter Hoffmann
Chapter
Part of the Springer Undergraduate Texts in Mathematics and Technology book series (SUMAT)

Abstarct

In this chapter we will focus on necessary and sufficient optimality conditions for constrained problems.

Keywords

Dual Problem Convex Cone Primal Problem Feasible Point Convex Optimization Problem 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

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    J. Franklin (1980): Methods of Mathematical Economics. Springer, Berlin, Heidelberg, New YorkGoogle Scholar
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    R. T. Rockafellar (1970): Convex Analysis. Princeton University Press, PrincetonGoogle Scholar
  3. Bo/Va.
    S. Boyd, L. Vandenberghe (2004): Convex Optimization. Cambridge University Press, CambridgeGoogle Scholar
  4. Ga/Hr.
    W. Gander, J. Hrebicek (eds.) (2004): Solving Problems in Scientific Computing using Maple and Matlab. Springer, Berlin, Heidelberg, New York. Chapter 6Google Scholar
  5. Br/Ti.
    J. Brinkhuis, V. Tikhomirov (2005): Optimization: Insights and Applications. Princeton University Press, PrincetonGoogle Scholar
  6. Pow 1.
    M. J. D. Powell (1977): Variable Metric Methods for Constrained Optimization. Report DAMTP 77/NA6, University of CambridgeGoogle Scholar
  7. Erik.
    J. Eriksson (1980): A Note on Solution of Large Sparse Maximum Entropy Problems with Linear Equality Constraints. Math. Progr. 18, pp. 146–154Google Scholar
  8. Cr/Sh.
    N. Cristianini, J. Shawe-Taylor (2000): Introduction to Support Vector Machines. Cambridge University Press, CambridgeGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  1. 1.Fak. Mathematik und Wirtschaftswissenschaften Inst. Numerische MathematikUniversität UlmUlmGermany
  2. 2.FB Mathematik und StatistikUniversität KonstanzKonstanzGermany

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