Journal of Optimization Theory and Applications

, Volume 21, Issue 2, pp 121–135

Generalized Lagrange multiplier technique for nonlinear programming

Authors

  • Y. Evtushenko
    • Computing Center of the USSR
    • Physico-Technical Institute
Contributed Papers

DOI: 10.1007/BF00932516

Cite this article as:
Evtushenko, Y. J Optim Theory Appl (1977) 21: 121. doi:10.1007/BF00932516

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 programmingmax-min problemsLagrange multiplier techniqueNewton's method

Copyright information

© Plenum Publishing Corporation 1977