Generalized Lagrange multiplier technique for nonlinear programming

Evtushenko Y (1977). Generalized Lagrange multiplier technique for nonlinear programming. Journal of Optimization Theory and Applications 21 (2): 121-135. DOI:10.1007/BF00932516.

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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.

Item Type: Article
Uncontrolled Keywords: Nonlinear programming; max-min problems; Lagrange multiplier technique; Newton's method
Research Programs: System and Decision Sciences - Core (SDS)
Depositing User: Romeo Molina
Date Deposited: 19 May 2016 07:09
Last Modified: 19 May 2016 07:09
URI: http://pure.iiasa.ac.at/13230

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