Research on trust-region algorithms for nonlinear programming
This report discusses research on the following topics: interior- point methods for linear programming; trust-region SQP newton's method for general nonlinear programming problems; trust-region SQP newton's method for large sparse nonlinear programming problems with applications to oil reservoir management; a unified approach to global convergence of trust-region methods for nonsmooth optimization; and SQP augmented lagrangian BRGS algorithm for constrained optimization. (LSP).
- Research Organization:
- Rice Univ., Houston, TX (United States)
- Sponsoring Organization:
- DOE; USDOE, Washington, DC (United States)
- DOE Contract Number:
- FG05-86ER25017
- OSTI ID:
- 5970506
- Report Number(s):
- DOE/ER/25017-5; ON: DE92005466
- Country of Publication:
- United States
- Language:
- English
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