Constraints for minimizing without any constraint.
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#include <Real_value_function_minimizer.hpp>
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bool | get_nlp_info (Ipopt::Index &n, Ipopt::Index &m, Ipopt::Index &nnz_jac_g, Ipopt::Index &nnz_h_lag, IndexStyleEnum &index_style) |
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bool | get_bounds_info (Ipopt::Index n, Ipopt::Number *x_l, Ipopt::Number *x_u, Ipopt::Index m, Ipopt::Number *g_l, Ipopt::Number *g_u) |
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bool | get_starting_point (Ipopt::Index n, bool init_x, Ipopt::Number *x, bool init_z, Ipopt::Number *z_L, Ipopt::Number *z_U, Ipopt::Index m, bool init_lambda, Ipopt::Number *lambda) |
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bool | eval_f (Ipopt::Index n, const Ipopt::Number *x, bool new_x, Ipopt::Number &obj_value) |
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bool | eval_grad_f (Ipopt::Index n, const Ipopt::Number *x, bool new_x, Ipopt::Number *grad_f) |
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bool | eval_g (Ipopt::Index n, const Ipopt::Number *x, bool new_x, Ipopt::Index m, Ipopt::Number *g) |
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bool | eval_jac_g (Ipopt::Index n, const Ipopt::Number *x, bool new_x, Ipopt::Index m, Ipopt::Index nele_jac, Ipopt::Index *iRow, Ipopt::Index *jCol, Ipopt::Number *values) |
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void | finalize_solution (Ipopt::SolverReturn status, Ipopt::Index n, const Ipopt::Number *x, const Ipopt::Number *z_L, const Ipopt::Number *z_U, Ipopt::Index m, const Ipopt::Number *g, const Ipopt::Number *lambda, Ipopt::Number obj_value, const Ipopt::IpoptData *ip_data, Ipopt::IpoptCalculatedQuantities *ip_cq) |
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template<class PointType, class RealValueFunction, class GradientFunction>
class SBL::CSB::T_Minimizer_parameters_without_constraint< PointType, RealValueFunction, GradientFunction >
Constraints for minimizing without any constraint.
Constraints for minimizing without any constraint
- Template Parameters
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PointType | Point type argument of the real value function. |
RealValueFunction | Functor taking a Point type and returning a value. |
GradientFunction | Gradient of the function represented by RealValueFunction. |
◆ T_Minimizer_parameters_without_constraint()
constructor initializing the init point
◆ eval_f()
bool eval_f |
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Ipopt::Index |
n, |
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const Ipopt::Number * |
x, |
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bool |
new_x, |
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Ipopt::Number & |
obj_value |
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Method to return the objective value
◆ eval_g()
bool eval_g |
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Ipopt::Index |
n, |
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const Ipopt::Number * |
x, |
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bool |
new_x, |
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Ipopt::Index |
m, |
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Ipopt::Number * |
g |
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Method to return the constraint residuals
◆ eval_grad_f()
bool eval_grad_f |
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Ipopt::Index |
n, |
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const Ipopt::Number * |
x, |
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bool |
new_x, |
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Ipopt::Number * |
grad_f |
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Method to return the gradient of the objective
◆ eval_jac_g()
bool eval_jac_g |
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Ipopt::Index |
n, |
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const Ipopt::Number * |
x, |
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bool |
new_x, |
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Ipopt::Index |
m, |
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Ipopt::Index |
nele_jac, |
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Ipopt::Index * |
iRow, |
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Ipopt::Index * |
jCol, |
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Ipopt::Number * |
values |
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Method to return: 1) The structure of the jacobian (if "values" is NULL) 2) The values of the jacobian (if "values" is not NULL)
◆ finalize_solution()
void finalize_solution |
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Ipopt::SolverReturn |
status, |
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Ipopt::Index |
n, |
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const Ipopt::Number * |
x, |
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const Ipopt::Number * |
z_L, |
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const Ipopt::Number * |
z_U, |
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Ipopt::Index |
m, |
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const Ipopt::Number * |
g, |
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const Ipopt::Number * |
lambda, |
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Ipopt::Number |
obj_value, |
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const Ipopt::IpoptData * |
ip_data, |
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Ipopt::IpoptCalculatedQuantities * |
ip_cq |
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This method is called when the algorithm is complete so the TNLP can store/write the solution
◆ get_bounds_info()
bool get_bounds_info |
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Ipopt::Index |
n, |
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Ipopt::Number * |
x_l, |
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Ipopt::Number * |
x_u, |
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Ipopt::Index |
m, |
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Ipopt::Number * |
g_l, |
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Ipopt::Number * |
g_u |
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Method to return the bounds for my problem
◆ get_nlp_info()
bool get_nlp_info |
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Ipopt::Index & |
n, |
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Ipopt::Index & |
m, |
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Ipopt::Index & |
nnz_jac_g, |
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Ipopt::Index & |
nnz_h_lag, |
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IndexStyleEnum & |
index_style |
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Method to return some info about the nlp
◆ get_starting_point()
bool get_starting_point |
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Ipopt::Index |
n, |
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bool |
init_x, |
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Ipopt::Number * |
x, |
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bool |
init_z, |
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Ipopt::Number * |
z_L, |
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Ipopt::Number * |
z_U, |
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Ipopt::Index |
m, |
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bool |
init_lambda, |
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Ipopt::Number * |
lambda |
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Method to return the starting point for the algorithm