SLATEC Common Mathematical Library -- Table of Contents

SECTION I. User-callable Routines
Category G. Optimization (search also classes K, L8)

         G2.  Constrained
         G4.  Service routines

G2.  Constrained
G2A.  Linear programming
G2A2.  Sparse matrix of constraints
 
          SPLP-S    Solve linear programming problems involving at
          DSPLP-D   most a few thousand constraints and variables.
                    Takes advantage of sparsity in the constraint matrix.
 
G2E.  Quadratic programming
 
          SBOCLS-S  Solve the bounded and constrained least squares
          DBOCLS-D  problem consisting of solving the equation
                              E*X = F  (in the least squares sense)
                     subject to the linear constraints
                                    C*X = Y.
 
          SBOLS-S   Solve the problem
          DBOLS-D        E*X = F (in the least  squares  sense)
                    with bounds on selected X values.
 
G2H.  General nonlinear programming
G2H1.  Simple bounds
 
          SBOCLS-S  Solve the bounded and constrained least squares
          DBOCLS-D  problem consisting of solving the equation
                              E*X = F  (in the least squares sense)
                     subject to the linear constraints
                                    C*X = Y.
 
          SBOLS-S   Solve the problem
          DBOLS-D        E*X = F (in the least  squares  sense)
                    with bounds on selected X values.
 
G2H2.  Linear equality or inequality constraints
 
          SBOCLS-S  Solve the bounded and constrained least squares
          DBOCLS-D  problem consisting of solving the equation
                              E*X = F  (in the least squares sense)
                     subject to the linear constraints
                                    C*X = Y.
 
          SBOLS-S   Solve the problem
          DBOLS-D        E*X = F (in the least  squares  sense)
                    with bounds on selected X values.
 
G4.  Service routines
G4C.  Check user-supplied derivatives
 
          CHKDER-S  Check the gradients of M nonlinear functions in N
          DCKDER-D  variables, evaluated at a point X, for consistency
                    with the functions themselves.