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...
Uloženo v:
| Vydáno v: | Nonlinear Programming s. 207 - 243 |
|---|---|
| Hlavní autor: | |
| Médium: | Kapitola |
| Jazyk: | angličtina |
| Vydáno: |
United States
Elsevier Inc
1970
Elsevier Science & Technology |
| Témata: | |
| ISBN: | 9780125970501, 148327246X, 9781483245638, 9781483272467, 1483245632, 0125970501 |
| On-line přístup: | Získat plný text |
| Tagy: |
Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
|
| Shrnutí: | 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). |
|---|---|
| ISBN: | 9780125970501 148327246X 9781483245638 9781483272467 1483245632 0125970501 |
| DOI: | 10.1016/B978-0-12-597050-1.50011-7 |

