User's guide for SOL/NPSOL: a Fortran package for nonlinear programming
This report forms the user's guide for Version 1.1 of SOL/NPSOL, a set of Fortran subroutines designed to minimize an abritary smooth function subject to constraints, which may include simple bounds on the variables, linear constraints and smooth nonlinear constraints. (NPSOL may also be used for unconstrained, bound-constrained and linearly constrained optimization.) The user must provide subroutines that define the objective and constraint functions and their gradients. All matrices are treated as dense, and hence NPSOL is not intended for large sparse problems. NPSOL uses a sequential quadratic programming (SQP) algorithm, in which the search direction is the solution of a quadratic programming (QP) subproblem. The algorithm treats bounds, linear constraints and nonlinear constraints separately. The Hessian of each QP subproblem is a positive-definite quasi-Newton approximation to the Hessian of an augmented Lagrangian function. The steplength at each iteration is required to produce a sufficient decrease in an augmented Lagrangian merit function. Each QP subproblem is solved using a quadratic programming package with several features that improve the efficiency of an SQP algorithm.
- Research Organization:
- Stanford Univ., CA (USA). Systems Optimization Lab.
- DOE Contract Number:
- AT03-76ER72018
- OSTI ID:
- 5731141
- Report Number(s):
- SOL-83-12; ON: DE83016903
- Resource Relation:
- Other Information: Portions are illegible in microfiche products
- Country of Publication:
- United States
- Language:
- English
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