This report forms the user's guide for Version 4.0 of NPSOL, a set of Fortran subroutines
designed to minimize a 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 (optionally) 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 the Lagrangian function. The
steplength at each iteration is required to produce a sufficient decrease in an augmented Lagrangian
merit function. Each QP subproblcm is solved using a quadratic programming package with several
features that improve the efficiency of an SQP
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