Couenne 0.5.8
CouenneTNLP.hpp
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1/* $Id: CouenneTNLP.hpp 893 2012-08-09 14:48:19Z pbelotti $
2 *
3 * Name: CouenneTNLP.hpp
4 * Authors: Pietro Belotti, Lehigh University
5 * Purpose: Definition of an NLP interface with gradient/Jacobian/etc
6 *
7 * This file is licensed under the Eclipse Public License (EPL)
8 */
9
10#ifndef COUENNETNLP_HPP
11#define COUENNETNLP_HPP
12
13#include "IpTNLP.hpp"
14#include "CouenneExprJac.hpp"
15#include "CouenneExprHess.hpp"
16#include "CouenneTypes.hpp"
17
18#include <vector>
19#include <set>
20
21namespace Couenne {
22
23 class CouenneProblem;
24 class CouenneSparseMatrix;
25
27 class CouenneTNLP: public Ipopt::TNLP {
28
29 public:
30
33
36
39
42
45
47 virtual ~CouenneTNLP ();
48
50 void setInitSol (const double *sol);
51
54 {return sol_;}
55
58 {return bestZ_;}
59
65 virtual bool get_nlp_info (Ipopt::Index& n,
66 Ipopt::Index& m,
67 Ipopt::Index& nnz_jac_g,
68 Ipopt::Index& nnz_h_lag,
69 enum Ipopt::TNLP::IndexStyleEnum& index_style);
70
78
84
89
97 bool init_x, Ipopt::Number* x,
98 bool init_z, Ipopt::Number* z_L, Ipopt::Number* z_U,
99 Ipopt::Index m,
100 bool init_lambda, Ipopt::Number* lambda);
101
103 virtual bool eval_f (Ipopt::Index n, const Ipopt::Number* x, bool new_x,
104 Ipopt::Number& obj_value);
105
107 virtual bool eval_grad_f (Ipopt::Index n, const Ipopt::Number* x,
108 bool new_x,
109 Ipopt::Number* grad_f);
110
112 virtual bool eval_g (Ipopt::Index n, const Ipopt::Number* x, bool new_x,
114
120 virtual bool eval_jac_g (Ipopt::Index n, const Ipopt::Number* x, bool new_x,
121 Ipopt::Index m, Ipopt::Index nele_jac, Ipopt::Index* iRow,
122 Ipopt::Index *jCol, Ipopt::Number* values);
123
133 virtual bool eval_h (Ipopt::Index n, const Ipopt::Number* x, bool new_x,
134 Ipopt::Number obj_factor, Ipopt::Index m, const Ipopt::Number* lambda,
135 bool new_lambda, Ipopt::Index nele_hess,
136 Ipopt::Index* iRow, Ipopt::Index* jCol, Ipopt::Number* values);
137
140 Ipopt::Index n, const Ipopt::Number* x, const Ipopt::Number* z_L, const Ipopt::Number* z_U,
141 Ipopt::Index m, const Ipopt::Number* g, const Ipopt::Number* lambda,
142 Ipopt::Number obj_value,
143 const Ipopt::IpoptData* ip_data,
145
149 virtual bool intermediate_callback (Ipopt::AlgorithmMode mode,
150 Ipopt::Index iter, Ipopt::Number obj_value,
151 Ipopt::Number inf_pr, Ipopt::Number inf_du,
152 Ipopt::Number mu, Ipopt::Number d_norm,
153 Ipopt::Number regularization_size,
154 Ipopt::Number alpha_du, Ipopt::Number alpha_pr,
155 Ipopt::Index ls_trials,
156 const Ipopt::IpoptData* ip_data,
158
172
174 virtual bool get_list_of_nonlinear_variables (Ipopt::Index num_nonlin_vars,
175 Ipopt::Index* pos_nonlin_vars);
176
179 virtual void setObjective (expression *newObj);
180
183 {return optHessian_;}
184
186 inline bool &getSaveOptHessian ()
187 {return saveOptHessian_;}
188
189 private:
190
192 CouenneProblem *problem_;
193
195 CouNumber *sol0_;
196
198 CouNumber *sol_;
199
201 CouNumber bestZ_;
202
204 std::vector <std::pair <int, expression *> > gradient_;
205
207 std::set <int> nonLinVars_;
208
210 ExprJac Jac_;
211
214 ExprHess *HLa_;
215
217 CouenneSparseMatrix *optHessian_;
218
220 bool saveOptHessian_;
221 };
222}
223
224#endif
Class for MINLP problems with symbolic information.
Class for sparse Matrixs (used in modifying distances in FP)
Class for handling NLPs using CouenneProblem.
Definition: CouenneTNLP.hpp:27
virtual bool get_nlp_info(Ipopt::Index &n, Ipopt::Index &m, Ipopt::Index &nnz_jac_g, Ipopt::Index &nnz_h_lag, enum 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_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 ~CouenneTNLP()
Destructor.
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.
CouenneTNLP(CouenneProblem *)
Constructor.
CouenneSparseMatrix *& optHessian()
Get methods.
void setInitSol(const double *sol)
set initial solution
CouenneTNLP & operator=(const CouenneTNLP &rhs)
Assignment.
CouenneTNLP()
Empty constructor.
CouNumber getSolValue()
returns value of the best solution
Definition: CouenneTNLP.hpp:57
virtual void setObjective(expression *newObj)
Change objective function and modify gradient expressions accordingly.
virtual Ipopt::Index get_number_of_nonlinear_variables()
bool & getSaveOptHessian()
set and get saveOptHessian_
virtual 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)
This method is called when the algorithm is complete so the TNLP can store/write the solution.
virtual bool intermediate_callback(Ipopt::AlgorithmMode mode, Ipopt::Index iter, Ipopt::Number obj_value, Ipopt::Number inf_pr, Ipopt::Number inf_du, Ipopt::Number mu, Ipopt::Number d_norm, Ipopt::Number regularization_size, Ipopt::Number alpha_du, Ipopt::Number alpha_pr, Ipopt::Index ls_trials, const Ipopt::IpoptData *ip_data, Ipopt::IpoptCalculatedQuantities *ip_cq)
Intermediate Callback method for the user.
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.
virtual bool get_constraints_linearity(Ipopt::Index m, Ipopt::TNLP::LinearityType *const_types)
return the constraint linearity.
virtual bool get_list_of_nonlinear_variables(Ipopt::Index num_nonlin_vars, Ipopt::Index *pos_nonlin_vars)
get real list
CouNumber * getSolution()
returns best solution (if it exists)
Definition: CouenneTNLP.hpp:53
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. x
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
CouenneTNLP(const CouenneTNLP &)
Copy constructor.
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
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.
virtual bool get_variables_linearity(Ipopt::Index n, Ipopt::TNLP::LinearityType *var_types)
return the variables linearity (TNLP::Linear or TNLP::NonLinear).
CouenneTNLP * clone()
Clone.
expression matrices.
Jacobian of the problem (computed through Couenne expression classes).
Expression base class.
general include file for different compilers
double CouNumber
main number type in Couenne
ipindex Index
ipnumber Number