Registration of problem sizes

Functions
integer(c_int) function	conopt::coidef_numvar (cntvect, numvar)
	defines the number of variables in the model.
integer(c_int) function	conopt::coidef_numcon (cntvect, numcon)
	defines the number of constraints in the model.
integer(c_int) function	conopt::coidef_numnz (cntvect, numnz)
	defines the number of nonzero elements in the Jacobian.
integer(c_int) function	conopt::coidef_numnlnz (cntvect, numnlnz)
	defines the Number of Nonlinear Nonzeros.
integer(c_int) function	conopt::coidef_numhess (cntvect, numhess)
	defines the Number of Hessian Nonzeros.
integer(c_int) function	conopt::coidef_optdir (cntvect, optdir)
	defines the Optimization Direction.
integer(c_int) function	conopt::coidef_objcon (cntvect, objcon)
	defines the Objective Constraint.
integer(c_int) function	conopt::coidef_objvar (cntvect, objvar)
	defines the Objective Variable.

Detailed Description

Before any model data can be loaded into CONOPT, the dimensions of the problem must be first specified.

This includes the number of variables, the number of constraints, the number of non-zeros, etc. The routines for registering the problem sizes are given in this section. These sizes are used in callbacks when loading the problem matrix and evaluating the first derivatives.

Function Documentation

coidef_numvar()

integer(c_int) function conopt::coidef_numvar	(	integer(c_int), dimension(*), intent(inout)	cntvect,
		integer(c_int), value	numvar )

defines the number of variables in the model.

Attention

Mandatory routine. The number must be positive.

defines the number of variables in the model. The number does not include any slack or artificial variables.

Parameters

cntvect	the control vector
numvar	the number of variables

Definition at line 96 of file conopt.f90.

coidef_numcon()

integer(c_int) function conopt::coidef_numcon	(	integer(c_int), dimension(*), intent(inout)	cntvect,
		integer(c_int), value	numcon )

defines the number of constraints in the model.

Attention

Mandatory routine. The number must be positive.

defines the number of constraints in the model. The number includes the objective function if the objective is defined as an expression (see coidef_objcon() and coidef_objvar()).

Parameters

cntvect	the control vector
numcon	the number of constraints

Definition at line 120 of file conopt.f90.

coidef_numnz()

integer(c_int) function conopt::coidef_numnz	(	integer(c_int), dimension(*), intent(inout)	cntvect,
		integer(c_int), value	numnz )

defines the number of nonzero elements in the Jacobian.

Attention

Mandatory routine. The number must be positive.

defines the number of nonzero elements in the Jacobian of the model (the matrix of first derivatives of all constraints with respect to all variables).

Parameters

cntvect	the control vector
numnz	the number of nonzero elements

Definition at line 143 of file conopt.f90.

coidef_numnlnz()

integer(c_int) function conopt::coidef_numnlnz	(	integer(c_int), dimension(*), intent(inout)	cntvect,
		integer(c_int), value	numnlnz )

defines the Number of Nonlinear Nonzeros.

Attention

Mandatory routine.

defines the number of nonlinear nonzeros in the Jacobian. The number is zero if the model is linear and positive if the model is nonlinear.

Parameters

cntvect	the control vector
numnlnz	the number of nonlinear nonzeros

Definition at line 166 of file conopt.f90.

coidef_numhess()

integer(c_int) function conopt::coidef_numhess	(	integer(c_int), dimension(*), intent(inout)	cntvect,
		integer(c_int), value	numhess )

defines the Number of Hessian Nonzeros.

defines the number of nonzeros in the Hessian. The number is zero if the model is linear and positive if the model is nonlinear.

Parameters

cntvect	the control vector
numhess	the number of nonzeros in Hessian

Definition at line 187 of file conopt.f90.

coidef_optdir()

integer(c_int) function conopt::coidef_optdir	(	integer(c_int), dimension(*), intent(inout)	cntvect,
		integer(c_int), value	optdir )

defines the Optimization Direction.

defines the optimization direction. OptDir = +1 defines maximization and OptDir = -1 defines minimization. Setting an optimization direction is optional. If no optimization direction is set, the CONOPT will search for a feasible solution and then stop.

Parameters

cntvect	the control vector
optdir	the optimization direction

Definition at line 212 of file conopt.f90.

coidef_objcon()

integer(c_int) function conopt::coidef_objcon	(	integer(c_int), dimension(*), intent(inout)	cntvect,
		integer(c_int), value	objcon )

defines the Objective Constraint.

Note

The constraint must be a Free Row, see argument TYPE in ReadMatrix in section ReadMatrix.

If both an objective variable and constraint are set, the last one set will be used in the optimization. You can turn a previously defined objective off by defining variable or constraint 0 as the objective (Fortran notation) or variable or constraint -1 (C notation).

Parameters

cntvect	the control vector
objcon	the index of the objective constraint

Definition at line 238 of file conopt.f90.

coidef_objvar()

integer(c_int) function conopt::coidef_objvar	(	integer(c_int), dimension(*), intent(inout)	cntvect,
		integer(c_int), value	objvar )

defines the Objective Variable.

Parameters

cntvect	the control vector
objvar	the index of the objective variable

Definition at line 256 of file conopt.f90.