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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| Published in: | Nonlinear Programming pp. 207 - 243 |
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| Main Author: | |
| Format: | Book Chapter |
| Language: | English |
| Published: |
United States
Elsevier Inc
1970
Elsevier Science & Technology |
| Subjects: | |
| ISBN: | 9780125970501, 148327246X, 9781483245638, 9781483272467, 1483245632, 0125970501 |
| Online Access: | Get full text |
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| Summary: | 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). |
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| ISBN: | 9780125970501 148327246X 9781483245638 9781483272467 1483245632 0125970501 |
| DOI: | 10.1016/B978-0-12-597050-1.50011-7 |