Journal of Optimization Theory and Applications

, Volume 21, Issue 2, pp 121–135 | Cite as

Generalized Lagrange multiplier technique for nonlinear programming

  • Y. Evtushenko
Contributed Papers

Abstract

Our aim here is to present numerical methods for solving a general nonlinear programming problem. These methods are based on transformation of a given constrained minimization problem into an unconstrained maximin problem. This transformation is done by using a generalized Lagrange multiplier technique. Such an approach permits us to use Newton's and gradient methods for nonlinear programming. Convergence proofs are provided, and some numerical results are given.

Key Words

Nonlinear programming max-min problems Lagrange multiplier technique Newton's method 

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Copyright information

© Plenum Publishing Corporation 1977

Authors and Affiliations

  • Y. Evtushenko
    • 1
    • 2
  1. 1.Computing Center of the USSRMoscowUSSR
  2. 2.Physico-Technical InstituteMoscowUSSR
  3. 3.International Institute for Applied Systems AnalysisSchloss LaxenburgLaxenburgAustria

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