A Second Order Method for the Linearly Constrained Nonlinear Programming Problem

An algorithm using second derivatives for solving the problem: minimize f(x) subject to Ax − b ≥ 0 is presented. Convergence to a Second-Order Kuhn Tucker Point is proved. If the strict second-order sufficiency conditions hold, the rate of convergence of the algorithm is shown to be superlinear or e...

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Vydané v:Nonlinear Programming s. 207 - 243
Hlavný autor: McCORMICK, GARTH P.
Médium: Kapitola
Jazyk:English
Vydavateľské údaje: United States Elsevier Inc 1970
Elsevier Science & Technology
Predmet:
Applied mathematics
ISBN:9780125970501, 148327246X, 9781483245638, 9781483272467, 1483245632, 0125970501
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Abstract An algorithm using second derivatives for solving the problem: minimize f(x) subject to Ax − b ≥ 0 is presented. Convergence to a Second-Order Kuhn Tucker Point is proved. If the strict second-order sufficiency conditions hold, the rate of convergence of the algorithm is shown to be superlinear or even quadratic with aLipschitz condition on the second derivatives of f(x).
AbstractList An algorithm using second derivatives for solving the problem: minimize f(x) subject to Ax − b ≥ 0 is presented. Convergence to a Second-Order Kuhn Tucker Point is proved. If the strict second-order sufficiency conditions hold, the rate of convergence of the algorithm is shown to be superlinear or even quadratic with aLipschitz condition on the second derivatives of f(x).
Author McCORMICK, GARTH P.
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PublicationSubtitle Proceedings of a Symposium Conducted by the Mathematics Research Center, the University of Wisconsin, Madison, May 4-6 1970
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Snippet An algorithm using second derivatives for solving the problem: minimize f(x) subject to Ax − b ≥ 0 is presented. Convergence to a Second-Order Kuhn Tucker...
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StartPage 207
SubjectTerms Applied mathematics
Title A Second Order Method for the Linearly Constrained Nonlinear Programming Problem
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