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NLP optimality conditions

  • Eligius M. T. Hendrix
  • Boglárka G.-Tóth
Chapter
Part of the Springer Optimization and Its Applications book series (SOIA, volume 37)

Abstract

After an optimization problem has been formulated (or during the formulation), methods can be used to determine an optimal plan x *. In the application of NLP algorithms, x * is approximated iteratively. The user normally indicates how close an optimum should be approximated. We will discuss this in Chapter 4.

Keywords

Saddle Point Stationary Point Quadratic Function Minimum Point Maximum Point 
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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Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  1. 1.Department of Computer ArchitectureMálaga UniversityMálagaSpain
  2. 2.Department of Differential EquationsBudapest University of Technology and EconomicsBudapestHungary

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