Contributed Papers

Journal of Optimization Theory and Applications

, Volume 21, Issue 2, pp 121-135

First online:

Generalized Lagrange multiplier technique for nonlinear programming

  • Y. EvtushenkoAffiliated withComputing Center of the USSRPhysico-Technical Institute

Rent the article at a discount

Rent now

* Final gross prices may vary according to local VAT.

Get Access


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