#include <OSBonminSolver.h>
Collaboration diagram for BonminProblem:
Public Member Functions | |
BonminProblem (OSInstance *osinstance_, OSOption *osoption_) | |
the BonminProblemclass constructor | |
virtual | ~BonminProblem () |
the BonminProblem class destructor | |
virtual bool | get_scaling_parameters (Number &obj_scaling, bool &use_x_scaling, Index n, Number *x_scaling, bool &use_g_scaling, Index m, Number *g_scaling) |
virtual const SosInfo * | sosConstraints () const |
virtual const BranchingInfo * | branchingInfo () const |
void | printSolutionAtEndOfAlgorithm () |
Overloaded functions specific to a TMINLP. | |
virtual bool | get_variables_types (Index n, VariableType *var_types) |
Pass the type of the variables (INTEGER, BINARY, CONTINUOUS) to the optimizer. | |
virtual bool | get_variables_linearity (Index n, Ipopt::TNLP::LinearityType *var_types) |
Pass info about linear and nonlinear variables. | |
virtual bool | get_constraints_linearity (Index m, Ipopt::TNLP::LinearityType *const_types) |
Pass the type of the constraints (LINEAR, NON_LINEAR) to the optimizer. | |
Overloaded functions defining a TNLP. | |
This group of function implement the various elements needed to define and solve a TNLP. They are the same as those in a standard Ipopt NLP problem | |
virtual bool | get_nlp_info (Index &n, Index &m, Index &nnz_jac_g, Index &nnz_h_lag, TNLP::IndexStyleEnum &index_style) |
Method to pass the main dimensions of the problem to Ipopt. | |
virtual bool | get_bounds_info (Index n, Number *x_l, Number *x_u, Index m, Number *g_l, Number *g_u) |
Method to return the bounds for my problem. | |
virtual bool | get_starting_point (Index n, bool init_x, Number *x, bool init_z, Number *z_L, Number *z_U, Index m, bool init_lambda, Number *lambda) |
Method to return the starting point for the algorithm. | |
virtual bool | eval_f (Index n, const Number *x, bool new_x, Number &obj_value) |
Method to return the objective value. | |
virtual bool | eval_grad_f (Index n, const Number *x, bool new_x, Number *grad_f) |
Method to return the gradient of the objective. | |
virtual bool | eval_g (Index n, const Number *x, bool new_x, Index m, Number *g) |
Method to return the constraint residuals. | |
virtual bool | eval_jac_g (Index n, const Number *x, bool new_x, Index m, Index nele_jac, Index *iRow, Index *jCol, Number *values) |
Method to return: 1) The structure of the jacobian (if "values" is NULL) 2) The values of the jacobian (if "values" is not NULL). | |
virtual bool | eval_h (Index n, const Number *x, bool new_x, Number obj_factor, Index m, const Number *lambda, bool new_lambda, Index nele_hess, Index *iRow, Index *jCol, Number *values) |
Method to return: 1) The structure of the hessian of the lagrangian (if "values" is NULL) 2) The values of the hessian of the lagrangian (if "values" is not NULL). | |
Solution Methods | |
virtual void | finalize_solution (TMINLP::SolverReturn status_, Index n, const Number *x, Number obj_value) |
Method called by Ipopt at the end of optimization. | |
Public Attributes | |
OSInstance * | osinstance |
OSOption * | osoption |
TMINLP::SolverReturn | status |
Private Attributes | |
bool | printSol_ |
std::string | bonminErrorMsg |
Definition at line 86 of file OSBonminSolver.h.
BonminProblem::BonminProblem | ( | OSInstance * | osinstance_, | |
OSOption * | osoption_ | |||
) |
the BonminProblemclass constructor
Definition at line 1018 of file OSBonminSolver.cpp.
References osinstance, osoption, and printSol_.
BonminProblem::~BonminProblem | ( | ) | [virtual] |
bool BonminProblem::get_variables_types | ( | Index | n, | |
VariableType * | var_types | |||
) | [virtual] |
Pass the type of the variables (INTEGER, BINARY, CONTINUOUS) to the optimizer.
n | size of var_types (has to be equal to the number of variables in the problem) | |
var_types | types of the variables (has to be filled by function). |
Definition at line 75 of file OSBonminSolver.cpp.
References OSInstance::getVariableNumber(), OSInstance::getVariableTypes(), INTEGER, and osinstance.
bool BonminProblem::get_variables_linearity | ( | Index | n, | |
Ipopt::TNLP::LinearityType * | var_types | |||
) | [virtual] |
Pass info about linear and nonlinear variables.
get an index map of the nonlinear variables and see which variable are in <nonlinearExpressions> element
iterate through and get an index of all variables that are in <nonlinearExpressions> element
Definition at line 101 of file OSBonminSolver.cpp.
References bonminErrorMsg, ErrorClass::errormsg, OSInstance::getAllNonlinearVariablesIndexMap(), OSInstance::initForAlgDiff(), and osinstance.
bool BonminProblem::get_constraints_linearity | ( | Index | m, | |
Ipopt::TNLP::LinearityType * | const_types | |||
) | [virtual] |
Pass the type of the constraints (LINEAR, NON_LINEAR) to the optimizer.
m | size of const_types (has to be equal to the number of constraints in the problem) | |
const_types | types of the constraints (has to be filled by function). |
Definition at line 141 of file OSBonminSolver.cpp.
References OSInstance::getNonlinearExpressionTreeModIndexes(), OSInstance::getNumberOfNonlinearExpressionTreeModIndexes(), and osinstance.
bool BonminProblem::get_nlp_info | ( | Index & | n, | |
Index & | m, | |||
Index & | nnz_jac_g, | |||
Index & | nnz_h_lag, | |||
TNLP::IndexStyleEnum & | index_style | |||
) | [virtual] |
Method to pass the main dimensions of the problem to Ipopt.
n | number of variables in problem. | |
m | number of constraints. | |
nnz_jac_g | number of nonzeroes in Jacobian of constraints system. | |
nnz_h_lag | number of nonzeroes in Hessian of the Lagrangean. | |
index_style | indicate wether arrays are numbered from 0 (C-style) or from 1 (Fortran). |
Definition at line 167 of file OSBonminSolver.cpp.
References bonminErrorMsg, OSInstance::bUseExpTreeForFunEval, ErrorClass::errormsg, OSInstance::getConstraintNumber(), OSInstance::getJacobianSparsityPattern(), OSInstance::getLagrangianHessianSparsityPattern(), OSInstance::getNumberOfNonlinearExpressions(), OSInstance::getNumberOfQuadraticTerms(), OSInstance::getVariableNumber(), SparseHessianMatrix::hessDimension, OSInstance::initForAlgDiff(), osinstance, and SparseJacobianMatrix::valueSize.
bool BonminProblem::get_bounds_info | ( | Index | n, | |
Number * | x_l, | |||
Number * | x_u, | |||
Index | m, | |||
Number * | g_l, | |||
Number * | g_u | |||
) | [virtual] |
Method to return the bounds for my problem.
Definition at line 225 of file OSBonminSolver.cpp.
References OSInstance::getConstraintLowerBounds(), OSInstance::getConstraintUpperBounds(), OSInstance::getVariableLowerBounds(), OSInstance::getVariableUpperBounds(), and osinstance.
bool BonminProblem::get_starting_point | ( | Index | n, | |
bool | init_x, | |||
Number * | x, | |||
bool | init_z, | |||
Number * | z_L, | |||
Number * | z_U, | |||
Index | m, | |||
bool | init_lambda, | |||
Number * | lambda | |||
) | [virtual] |
Method to return the starting point for the algorithm.
Definition at line 265 of file OSBonminSolver.cpp.
References DEBUG, OSOption::getInitVarValuesSparse(), OSOption::getNumberOfInitVarValues(), OSInstance::getVariableNumber(), InitVarValue::idx, OSInstance::instanceData, Variable::lb, OSDBL_MAX, osinstance, osoption, Variable::ub, InitVarValue::value, Variables::var, and InstanceData::variables.
bool BonminProblem::eval_f | ( | Index | n, | |
const Number * | x, | |||
bool | new_x, | |||
Number & | obj_value | |||
) | [virtual] |
Method to return the objective value.
Definition at line 392 of file OSBonminSolver.cpp.
References bonminErrorMsg, OSInstance::calculateAllObjectiveFunctionValues(), ErrorClass::errormsg, OSInstance::getObjectiveNumber(), OSInstance::instanceData, Objective::maxOrMin, Objectives::obj, InstanceData::objectives, and osinstance.
bool BonminProblem::eval_grad_f | ( | Index | n, | |
const Number * | x, | |||
bool | new_x, | |||
Number * | grad_f | |||
) | [virtual] |
Method to return the gradient of the objective.
Definition at line 411 of file OSBonminSolver.cpp.
References bonminErrorMsg, OSInstance::calculateObjectiveFunctionGradient(), ErrorClass::errormsg, OSInstance::getObjectiveNumber(), OSInstance::instanceData, Objective::maxOrMin, Objectives::obj, InstanceData::objectives, and osinstance.
bool BonminProblem::eval_g | ( | Index | n, | |
const Number * | x, | |||
bool | new_x, | |||
Index | m, | |||
Number * | g | |||
) | [virtual] |
Method to return the constraint residuals.
Definition at line 440 of file OSBonminSolver.cpp.
References bonminErrorMsg, OSInstance::calculateAllConstraintFunctionValues(), ErrorClass::errormsg, and osinstance.
bool BonminProblem::eval_jac_g | ( | Index | n, | |
const Number * | x, | |||
bool | new_x, | |||
Index | m, | |||
Index | nele_jac, | |||
Index * | iRow, | |||
Index * | jCol, | |||
Number * | values | |||
) | [virtual] |
Method to return: 1) The structure of the jacobian (if "values" is NULL) 2) The values of the jacobian (if "values" is not NULL).
Definition at line 458 of file OSBonminSolver.cpp.
References bonminErrorMsg, ErrorClass::errormsg, OSInstance::getJacobianSparsityPattern(), SparseJacobianMatrix::indexes, osinstance, and SparseJacobianMatrix::starts.
bool BonminProblem::eval_h | ( | Index | n, | |
const Number * | x, | |||
bool | new_x, | |||
Number | obj_factor, | |||
Index | m, | |||
const Number * | lambda, | |||
bool | new_lambda, | |||
Index | nele_hess, | |||
Index * | iRow, | |||
Index * | jCol, | |||
Number * | values | |||
) | [virtual] |
Method to return: 1) The structure of the hessian of the lagrangian (if "values" is NULL) 2) The values of the hessian of the lagrangian (if "values" is not NULL).
Definition at line 508 of file OSBonminSolver.cpp.
References bonminErrorMsg, OSInstance::calculateLagrangianHessian(), ErrorClass::errormsg, OSInstance::getLagrangianHessianSparsityPattern(), SparseHessianMatrix::hessColIdx, SparseHessianMatrix::hessRowIdx, SparseHessianMatrix::hessValues, and osinstance.
bool BonminProblem::get_scaling_parameters | ( | Number & | obj_scaling, | |
bool & | use_x_scaling, | |||
Index | n, | |||
Number * | x_scaling, | |||
bool & | use_g_scaling, | |||
Index | m, | |||
Number * | g_scaling | |||
) | [virtual] |
Definition at line 557 of file OSBonminSolver.cpp.
void BonminProblem::finalize_solution | ( | TMINLP::SolverReturn | status_, | |
Index | n, | |||
const Number * | x, | |||
Number | obj_value | |||
) | [virtual] |
Method called by Ipopt at the end of optimization.
Definition at line 577 of file OSBonminSolver.cpp.
References status.
virtual const SosInfo* BonminProblem::sosConstraints | ( | ) | const [inline, virtual] |
Definition at line 198 of file OSBonminSolver.h.
virtual const BranchingInfo* BonminProblem::branchingInfo | ( | ) | const [inline, virtual] |
Definition at line 199 of file OSBonminSolver.h.
void BonminProblem::printSolutionAtEndOfAlgorithm | ( | ) | [inline] |
Definition at line 98 of file OSBonminSolver.h.
Referenced by BonminProblem(), eval_f(), eval_g(), eval_grad_f(), eval_h(), eval_jac_g(), get_bounds_info(), get_constraints_linearity(), get_nlp_info(), get_starting_point(), get_variables_linearity(), and get_variables_types().
Definition at line 100 of file OSBonminSolver.h.
Referenced by BonminProblem(), and get_starting_point().
TMINLP::SolverReturn BonminProblem::status |
bool BonminProblem::printSol_ [private] |
Definition at line 209 of file OSBonminSolver.h.
Referenced by BonminProblem(), and printSolutionAtEndOfAlgorithm().
std::string BonminProblem::bonminErrorMsg [private] |
Definition at line 229 of file OSBonminSolver.h.
Referenced by eval_f(), eval_g(), eval_grad_f(), eval_h(), eval_jac_g(), get_nlp_info(), and get_variables_linearity().