NN Models for General Nonlinear Programming

  • Xiang-Sun Zhang
Part of the Nonconvex Optimization and Its Applications book series (NOIA, volume 46)


A general nonlinear programming problem is formulated as:
$$\begin{gathered} Minimizef(x) \hfill \\ subjecttog(x) \leqslant 0 \hfill \\ h(x) = 0 \hfill \\ x \in \Omega \hfill \\ \end{gathered} $$
where Ω is a subset of ℝ n or simply Ω = ℝ n . When function g(x), h(x) do not appear in Eq. (11.1), we call it a general unconstrained nonlinear programming problem:
$$\begin{gathered} Minimize\;f(x) \hfill \\ subject\;to \hfill \\ \end{gathered} $$
We call a neural network designed as a solver of general nonlinear programming problems a NP net.


Neural Network Initial Point Synaptic Weight Quadratic Programming Problem Nonlinear Programming 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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Copyright information

© Springer Science+Business Media Dordrecht 2000

Authors and Affiliations

  • Xiang-Sun Zhang
    • 1
  1. 1.Academy of Mathematics and Systems, Institute of Applied MathematicsChinese Academy of SciencesChina

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