Generalized Lagrange Multiplier Technique for Nonlinear Programming

Evtushenko Y (1974). Generalized Lagrange Multiplier Technique for Nonlinear Programming. IIASA Working Paper. IIASA, Laxenburg, Austria: WP-74-071


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The numerical methods we present are based on transforming a given constrained minimization problem into an unconstrained maximin problem. This transformation is accomplished by utilizing generalized Lagrange multipler 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: Monograph (IIASA Working Paper)
Research Programs: System and Decision Sciences - Core (SDS)
Depositing User: IIASA Import
Date Deposited: 15 Jan 2016 01:40
Last Modified: 14 Mar 2018 15:16

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