10 #ifndef TMINLPLinObj_H
11 #define TMINLPLinObj_H
55 virtual bool get_nlp_info(Ipopt::Index&
n, Ipopt::Index&
m, Ipopt::Index& nnz_jac_g,
56 Ipopt::Index& nnz_h_lag, Ipopt::TNLP::IndexStyleEnum& index_style);
61 bool& use_x_scaling, Ipopt::Index n,
62 Ipopt::Number* x_scaling,
63 bool& use_g_scaling, Ipopt::Index m,
64 Ipopt::Number* g_scaling);
72 return tminlp_->get_variables_types(n - 1, var_types);
78 Ipopt::TNLP::LinearityType* const_types);
83 virtual bool get_bounds_info(Ipopt::Index n, Ipopt::Number* x_l, Ipopt::Number* x_u,
84 Ipopt::Index m, Ipopt::Number* g_l, Ipopt::Number* g_u);
90 bool init_z, Ipopt::Number* z_L, Ipopt::Number* z_U,
91 Ipopt::Index m,
bool init_lambda,
92 Ipopt::Number* lambda);
96 virtual bool eval_f(Ipopt::Index n,
const Ipopt::Number*
x,
bool new_x,
97 Ipopt::Number& obj_value){
104 virtual bool eval_grad_f(Ipopt::Index n,
const Ipopt::Number*
x,
bool new_x,
105 Ipopt::Number* grad_f){
109 for(
int i = 0 ; i <
n ; i++){
116 virtual bool eval_g(Ipopt::Index n,
const Ipopt::Number*
x,
bool new_x,
117 Ipopt::Index m, Ipopt::Number*
g);
122 virtual bool eval_jac_g(Ipopt::Index n,
const Ipopt::Number*
x,
bool new_x,
123 Ipopt::Index m, Ipopt::Index nele_jac, Ipopt::Index* iRow,
124 Ipopt::Index *jCol, Ipopt::Number*
values);
129 virtual bool eval_h(Ipopt::Index n,
const Ipopt::Number*
x,
bool new_x,
130 Ipopt::Number obj_factor, Ipopt::Index m,
const Ipopt::Number* lambda,
131 bool new_lambda, Ipopt::Index nele_hess,
132 Ipopt::Index* iRow, Ipopt::Index* jCol, Ipopt::Number*
values);
135 virtual bool eval_gi(Ipopt::Index n,
const Ipopt::Number*
x,
bool new_x,
136 Ipopt::Index i, Ipopt::Number& gi);
140 virtual bool eval_grad_gi(Ipopt::Index n,
const Ipopt::Number*
x,
bool new_x,
141 Ipopt::Index i, Ipopt::Index& nele_grad_gi, Ipopt::Index* jCol,
148 bool r_val =
tminlp_->get_variables_linearity(n-1, c);
158 Ipopt::Index n,
const Ipopt::Number*
x, Ipopt::Number obj_value){
159 return tminlp_->finalize_solution(status, n - 1, x,
166 return tminlp_->branchingInfo();
172 return tminlp_->sosConstraints();
183 return tminlp_->hasUpperBoundingObjective();}
187 Ipopt::Number& obj_value){
189 return tminlp_->eval_upper_bound_f(n - 1, x, obj_value); }
int nnz_jac_
number of non-zeroes in the jacobian of the transformed MINLP.
virtual bool eval_h(Ipopt::Index n, const Ipopt::Number *x, bool new_x, Ipopt::Number obj_factor, Ipopt::Index m, const Ipopt::Number *lambda, bool new_lambda, Ipopt::Index nele_hess, Ipopt::Index *iRow, Ipopt::Index *jCol, Ipopt::Number *values)
Return the hessian of the lagrangian.
Base class for all MINLPs that use a standard triplet matrix form and dense vectors.
Ipopt::SmartPtr< TMINLP > tminlp()
return pointer to tminlp_.
int n_
Ipopt::Number of variables in the transformed MINLP.
virtual const PerturbInfo * perturbInfo() const
Use tminlp_ function.
virtual bool get_constraints_linearity(Ipopt::Index m, Ipopt::TNLP::LinearityType *const_types)
Return the constraints linearity.
virtual bool get_scaling_parameters(Ipopt::Number &obj_scaling, bool &use_x_scaling, Ipopt::Index n, Ipopt::Number *x_scaling, bool &use_g_scaling, Ipopt::Index m, Ipopt::Number *g_scaling)
Return scaling parameters.
virtual const BranchingInfo * branchingInfo() const
Use tminlp_ function.
virtual const SosInfo * sosConstraints() const
Use tminlp_ function.
bool IsValid(const OSSmartPtr< U > &smart_ptr)
int m_
Ipopt::Number of constraints in the transformed MINLP.
Class to store sos constraints for model.
virtual bool eval_g(Ipopt::Index n, const Ipopt::Number *x, bool new_x, Ipopt::Index m, Ipopt::Number *g)
Return the vector of constraint values.
TMINLPLinObj()
Default constructor.
void gutsOfDestructor()
Reset all data.
virtual bool eval_grad_gi(Ipopt::Index n, const Ipopt::Number *x, bool new_x, Ipopt::Index i, Ipopt::Index &nele_grad_gi, Ipopt::Index *jCol, Ipopt::Number *values)
Compute the structure or values of the gradient for one constraint.
From a TMINLP, this class adapts to another TMINLP where the original objective is transformed into a...
Ipopt::SmartPtr< TMINLP > tminlp_
Reference TMINLP which is to be relaxed.
virtual bool eval_f(Ipopt::Index n, const Ipopt::Number *x, bool new_x, Ipopt::Number &obj_value)
Return the value of the objective function.
virtual bool get_variables_linearity(Ipopt::Index n, Ipopt::TNLP::LinearityType *c)
overload this method to provide the variables linearity.
virtual bool hasUpperBoundingObjective()
Use tminlp_ function.
SolverReturn
Return statuses of algorithm.
virtual bool eval_grad_f(Ipopt::Index n, const Ipopt::Number *x, bool new_x, Ipopt::Number *grad_f)
Return the vector of the gradient of the objective w.r.t.
virtual void finalize_solution(TMINLP::SolverReturn status, Ipopt::Index n, const Ipopt::Number *x, Ipopt::Number obj_value)
Use tminlp_ function.
virtual 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)
Return the information about the bound on the variables and constraints.
virtual bool hasLinearObjective()
Say if problem has a linear objective (for OA)
virtual bool get_nlp_info(Ipopt::Index &n, Ipopt::Index &m, Ipopt::Index &nnz_jac_g, Ipopt::Index &nnz_h_lag, Ipopt::TNLP::IndexStyleEnum &index_style)
Return the number of variables and constraints, and the number of non-zeros in the jacobian and the h...
virtual 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)
Return the starting point.
void setTminlp(Ipopt::SmartPtr< TMINLP > tminlp)
set reference TMINLP
int offset_
offset for jacobian.
virtual bool get_variables_types(Ipopt::Index n, VariableType *var_types)
Get the variable type.
Stores branching priorities information.
void fint fint fint real fint real real real real real real * g
virtual bool eval_gi(Ipopt::Index n, const Ipopt::Number *x, bool new_x, Ipopt::Index i, Ipopt::Number &gi)
Compute the value of a single constraint.
virtual 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)
Return the jacobian of the constraints.
Class to store perturbation radii for variables in the model.
virtual bool eval_upper_bound_f(Ipopt::Index n, const Ipopt::Number *x, Ipopt::Number &obj_value)
Use tminlp_ function.
virtual ~TMINLPLinObj()
destructor.
VariableType
Type of the variables.
void fint fint fint real fint real * x