Quadratically convergent techniques in linearly constrained optimization

descriptionPublicationkeyboard_double_arrow_right Article 01 May 1974 English Publisher:WileyJournal:AIChE Journal, volume 20, pages 555-563 (issn: 0001-1541, eissn: 1547-5905,

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Authors: Gregory J. Husen; James M. Eakman;

doi: 10.1002/aic.690200317

Quadratically convergent techniques in linearly constrained optimization

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Abstract

AbstractMethods for the solution of linearly constrained optimization of a nonlinear objective function are presented and compared. The methods of Fletcher‐Reeves, Fletcher, and Powell are used to generate search directions in the decision variable space. Generalized Kuhn‐Tucker conditions are presented and used to check for a local minimum.

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