Generalized Lagrange multiplier technique for nonlinear programming
- Y. Evtushenko
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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.
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- Generalized Lagrange multiplier technique for nonlinear programming
Journal of Optimization Theory and Applications
Volume 21, Issue 2 , pp 121-135
- Cover Date
- Print ISSN
- Online ISSN
- Kluwer Academic Publishers-Plenum Publishers
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- Nonlinear programming
- max-min problems
- Lagrange multiplier technique
- Newton's method
- Industry Sectors
- Y. Evtushenko (1) (2)
- Author Affiliations
- 1. Computing Center of the USSR, Moscow, USSR
- 2. Physico-Technical Institute, Moscow, USSR