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Systems and Management Science by Extremal Methods pp 205–223Cite as

A Tutorial on Parametric Nonlinear Programming Sensitivity and Stability Analysis

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Abstract

In this chapter, we will consider general parametric nonlinear programming (NLP) problems of the form

$$\begin{array}{*{20}{c}} \hfill {P(\varepsilon )} & \hfill {\mathop{{minimize}}\limits_{x} f(x,\varepsilon ) s.t. {g_{i}}(x,\varepsilon ) \geqslant 0,} & \hfill {i = 1, \ldots ,m,} \\ \hfill {} & \hfill {{h_{j}}(x,\varepsilon ) = 0,} & \hfill {j = 1, \ldots ,p,} \\ \end{array}$$

where f, g i , h j : R n × R r → R 1 and ε ∈ R r is a perturbation parameter.

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Authors
  1. Anthony V. Fiacco
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  2. Jerzy Kyparisis
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Editor information

Editors and Affiliations

  1. IC2 Institute, 2815 San Gabriel, 78705-3954, Austin, TX, USA

    Fred Young Phillips

  2. MRCA Information Services, 3001 North Lamar #110, 78705, Austin, TX, USA

    John James Rousseau

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© 1992 Springer Science+Business Media New York

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Fiacco, A.V., Kyparisis, J. (1992). A Tutorial on Parametric Nonlinear Programming Sensitivity and Stability Analysis. In: Phillips, F.Y., Rousseau, J.J. (eds) Systems and Management Science by Extremal Methods. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-3600-0_14

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  • DOI: https://doi.org/10.1007/978-1-4615-3600-0_14

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4613-6599-0

  • Online ISBN: 978-1-4615-3600-0

  • eBook Packages: Springer Book Archive

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