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Diffstat (limited to 'build/Bonmin/include/coin/BonTMINLP2TNLP.hpp')
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diff --git a/build/Bonmin/include/coin/BonTMINLP2TNLP.hpp b/build/Bonmin/include/coin/BonTMINLP2TNLP.hpp deleted file mode 100644 index 7523fc1..0000000 --- a/build/Bonmin/include/coin/BonTMINLP2TNLP.hpp +++ /dev/null @@ -1,509 +0,0 @@ -// (C) Copyright International Business Machines Corporation and Carnegie Mellon University 2004, 2006 -// All Rights Reserved. -// This code is published under the Eclipse Public License. -// -// Authors : -// Pierre Bonami, Carnegie Mellon University, -// Carl D. Laird, Carnegie Mellon University, -// Andreas Waechter, International Business Machines Corporation -// -// Date : 12/01/2004 - -#ifndef __TMINLP2TNLP_HPP__ -#define __TMINLP2TNLP_HPP__ - -#include "IpTNLP.hpp" -#include "BonTMINLP.hpp" -#include "IpSmartPtr.hpp" -#include "IpIpoptApplication.hpp" -#include "IpOptionsList.hpp" -#include "BonTypes.hpp" - -namespace Bonmin -{ - class IpoptInteriorWarmStarter; - - /** This is an adapter class that converts a TMINLP to - * a TNLP to be solved by Ipopt. It allows an external - * caller to modify the bounds of variables, allowing - * the treatment of binary and integer variables as - * relaxed, or fixed - */ - class TMINLP2TNLP : public Ipopt::TNLP - { - public: - /**@name Constructors/Destructors */ - //@{ - TMINLP2TNLP(const Ipopt::SmartPtr<TMINLP> tminlp -#ifdef WARM_STARTER - , - const OptionsList& options -#endif - ); - - /** Copy Constructor - * \warning source and copy point to the same tminlp_. - */ - TMINLP2TNLP(const TMINLP2TNLP&); - - /** virtual copy .*/ - virtual TMINLP2TNLP * clone() const{ - return new TMINLP2TNLP(*this);} - - /** Default destructor */ - virtual ~TMINLP2TNLP(); - //@} - - /**@name Methods to modify the MINLP and form the NLP */ - //@{ - - /** Get the number of variables */ - inline Ipopt::Index num_variables() const - { - assert(x_l_.size() == x_u_.size()); - return static_cast<int>(x_l_.size()); - } - - /** Get the number of constraints */ - inline Ipopt::Index num_constraints() const - { - assert(g_l_.size() == g_u_.size()); - return static_cast<int>(g_l_.size()); - } - /** Get the nomber of nz in hessian */ - Ipopt::Index nnz_h_lag() - { - return nnz_h_lag_; - } - /** Get the variable types */ - const TMINLP::VariableType* var_types() - { - return &var_types_[0]; - } - - /** Get the current values for the lower bounds */ - const Ipopt::Number* x_l() - { - return &x_l_[0]; - } - /** Get the current values for the upper bounds */ - const Ipopt::Number* x_u() - { - return &x_u_[0]; - } - - /** Get the original values for the lower bounds */ - const Ipopt::Number* orig_x_l() const - { - return &orig_x_l_[0]; - } - /** Get the original values for the upper bounds */ - const Ipopt::Number* orig_x_u() const - { - return orig_x_u_(); - } - - /** Get the current values for constraints lower bounds */ - const Ipopt::Number* g_l() - { - return g_l_(); - } - /** Get the current values for constraints upper bounds */ - const Ipopt::Number* g_u() - { - return g_u_(); - } - - /** get the starting primal point */ - const Ipopt::Number * x_init() const - { - return x_init_(); - } - - /** get the user provided starting primal point */ - const Ipopt::Number * x_init_user() const - { - return x_init_user_(); - } - - /** get the starting dual point */ - const Ipopt::Number * duals_init() const - { - return duals_init_; - } - - /** get the solution values */ - const Ipopt::Number* x_sol() const - { - return x_sol_(); - } - - /** get the g solution (activities) */ - const Ipopt::Number* g_sol() const - { - return g_sol_(); - } - - /** get the dual values */ - const Ipopt::Number* duals_sol() const - { - return duals_sol_(); - } - - /** Get Optimization status */ - Ipopt::SolverReturn optimization_status() const - { - return return_status_; - } - - /** Get the objective value */ - Ipopt::Number obj_value() const - { - return obj_value_; - } - - /** Manually set objective value. */ - void set_obj_value(Ipopt::Number value) - { - obj_value_ = value; - } - - /** force solution to be fractionnal.*/ - void force_fractionnal_sol(); - - /** Change the bounds on the variables */ - void SetVariablesBounds(Ipopt::Index n, - const Ipopt::Number * x_l, - const Ipopt::Number * x_u); - - /** Change the lower bound on the variables */ - void SetVariablesLowerBounds(Ipopt::Index n, - const Ipopt::Number * x_l); - - /** Change the upper bound on the variable */ - void SetVariablesUpperBounds(Ipopt::Index n, - const Ipopt::Number * x_u); - - /** Change the bounds on the variable */ - void SetVariableBounds(Ipopt::Index var_no, Ipopt::Number x_l, Ipopt::Number x_u); - - /** Change the lower bound on the variable */ - void SetVariableLowerBound(Ipopt::Index var_no, Ipopt::Number x_l); - - /** Change the upper bound on the variable */ - void SetVariableUpperBound(Ipopt::Index var_no, Ipopt::Number x_u); - - /** reset the starting point to original one. */ - void resetStartingPoint(); - - /** set the starting point to x_init */ - void setxInit(Ipopt::Index n,const Ipopt::Number* x_init); - - /** set the dual starting point to duals_init */ - void setDualsInit(Ipopt::Index n, const Ipopt::Number* duals_init); - - /** xInit has been set? - * \return 0 if not, 1 if only primal 2 if primal dual.*/ - int has_x_init(){ - if(x_init_.empty()) return 0; - if(duals_init_) return 2; - return 1; - } - /** Set the contiuous solution */ - void Set_x_sol(Ipopt::Index n, const Ipopt::Number* x_sol); - - /** Set the contiuous dual solution */ - void Set_dual_sol(Ipopt::Index n, const Ipopt::Number* dual_sol); - - /** Change the type of the variable */ - void SetVariableType(Ipopt::Index n, TMINLP::VariableType type); - //@} - /** Procedure to ouptut relevant informations to reproduce a sub-problem. - Compare the current problem to the problem to solve - and writes files with bounds which have changed and current starting point. - */ - void outputDiffs(const std::string& probName, const std::string* varNames); - - /**@name methods to gather information about the NLP */ - //@{ - /** This call is just passed onto the TMINLP object */ - virtual bool get_nlp_info(Ipopt::Index& n, Ipopt::Index& m, Ipopt::Index& nnz_jac_g, - Ipopt::Index& nnz_h_lag, - TNLP::IndexStyleEnum& index_style); - - /** The caller is allowed to modify the bounds, so this - * method returns the internal bounds information - */ - 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); - - /** Returns the constraint linearity. - * array should be alocated with length at least m..*/ - virtual bool get_constraints_linearity(Ipopt::Index m, LinearityType* const_types) - { - return tminlp_->get_constraints_linearity(m, const_types); - } - - /** Returns the variables linearity. - * array should be alocated with length at least n..*/ - virtual bool get_variables_linearity(Ipopt::Index n, LinearityType* var_types) - { - return tminlp_->get_variables_linearity(n, var_types); - } - - /** returns true if objective is linear.*/ - virtual bool hasLinearObjective(){return tminlp_->hasLinearObjective();} - /** Method called by Ipopt to get the starting point. The bools - * init_x and init_lambda are both inputs and outputs. As inputs, - * they indicate whether or not the algorithm wants you to - * initialize x and lambda respectively. If, for some reason, the - * algorithm wants you to initialize these and you cannot, set - * the respective bool to false. - */ - 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); - - /** Method that returns scaling parameters. - */ - 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); - - - /** Methat that returns an Ipopt IteratesVector that has the - * starting point for all internal varibles. */ - virtual bool get_warm_start_iterate(Ipopt::IteratesVector& warm_start_iterate); - - /** Returns the value of the objective function in x*/ - virtual bool eval_f(Ipopt::Index n, const Ipopt::Number* x, bool new_x, - Ipopt::Number& obj_value); - - /** Returns the vector of the gradient of - * the objective w.r.t. x */ - virtual bool eval_grad_f(Ipopt::Index n, const Ipopt::Number* x, bool new_x, - Ipopt::Number* grad_f); - - /** Returns the vector of constraint values in x*/ - virtual bool eval_g(Ipopt::Index n, const Ipopt::Number* x, bool new_x, - Ipopt::Index m, Ipopt::Number* g); - - /** Returns the jacobian of the - * constraints. The vectors iRow and jCol only need to be set - * once. The first call is used to set the structure only (iRow - * and jCol will be non-NULL, and values will be NULL) For - * subsequent calls, iRow and jCol will be NULL. */ - 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); - - /** compute the value of a single constraint */ - virtual bool eval_gi(Ipopt::Index n, const Ipopt::Number* x, bool new_x, - Ipopt::Index i, Ipopt::Number& gi); - /** compute the structure or values of the gradient for one - constraint */ - 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); - - /** Return the hessian of the - * lagrangian. The vectors iRow and jCol only need to be set once - * (during the first call). The first call is used to set the - * structure only (iRow and jCol will be non-NULL, and values - * will be NULL) For subsequent calls, iRow and jCol will be - * NULL. This matrix is symmetric - specify the lower diagonal - * only */ - 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); - //@} - - /** @name Solution Methods */ - //@{ - /** This method is called when the algorithm is complete so the TNLP can store/write the solution */ - 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); - /** Intermediate Callback method for the user. Providing dummy - * default implementation. For details see IntermediateCallBack - * in IpNLP.hpp. */ - 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); - //@} - - /** Method called to check wether a problem has still some variable not fixed. If there are no more - unfixed vars, checks wether the solution given by the bounds is feasible.*/ - - /** @name Methods for setting and getting the warm starter */ - //@{ - void SetWarmStarter(Ipopt::SmartPtr<IpoptInteriorWarmStarter> warm_starter); - - Ipopt::SmartPtr<IpoptInteriorWarmStarter> GetWarmStarter(); - - //@} - - /** Say if has a specific function to compute upper bounds*/ - virtual bool hasUpperBoundingObjective(){ - return tminlp_->hasUpperBoundingObjective();} - - /** Evaluate the upper bounding function at given point and store the result.*/ - double evaluateUpperBoundingFunction(const double * x); - - /** \name Cuts management. */ - /** Methods are not implemented at this point. But I need the interface.*/ - //@{ - - - /** Add some linear cuts to the problem formulation (not implemented yet in base class).*/ - virtual void addCuts(unsigned int numberCuts, const OsiRowCut ** cuts){ - if(numberCuts > 0) - throw CoinError("BonTMINLP2TNLP", "addCuts", "Not implemented");} - - - /** Add some cuts to the problem formulaiton (handles Quadratics).*/ - virtual void addCuts(const OsiCuts &cuts){ - if(cuts.sizeRowCuts() > 0 || cuts.sizeColCuts() > 0) - throw CoinError("BonTMINLP2TNLP", "addCuts", "Not implemented");} - - /** Remove some cuts to the formulation */ - virtual void removeCuts(unsigned int number ,const int * toRemove){ - if(number > 0) - throw CoinError("BonTMINLP2TNLP", "removeCuts", "Not implemented");} - - //@} - - - /** Access array describing constraint to which perspectives should be applied.*/ - virtual const int * get_const_xtra_id() const{ - return tminlp_->get_const_xtra_id(); - } - - /** Round and check the current solution, return norm inf of constraint violation.*/ - double check_solution(OsiObject ** objects = 0, int nObjects = -1); - protected: - /** \name These should be modified in derived class to always maintain there correctness. - They are directly queried by OsiTMINLPInterface without virtual function for - speed.*/ - /** @{ */ - /// Types of the variable (TMINLP::CONTINUOUS, TMINLP::INTEGER, TMINLP::BINARY). - vector<TMINLP::VariableType> var_types_; - /// Current lower bounds on variables - vector<Ipopt::Number> x_l_; - /// Current upper bounds on variables - vector<Ipopt::Number> x_u_; - /// Original lower bounds on variables - vector<Ipopt::Number> orig_x_l_; - /// Original upper bounds on variables - vector<Ipopt::Number> orig_x_u_; - /// Lower bounds on constraints values - vector<Ipopt::Number> g_l_; - /// Upper bounds on constraints values - vector<Ipopt::Number> g_u_; - /// Initial primal point - vector<Ipopt::Number> x_init_; - /** Initial values for all dual multipliers (constraints then lower bounds then upper bounds) */ - Ipopt::Number * duals_init_; - /// User-provideed initial prmal point - vector<Ipopt::Number> x_init_user_; - /// Optimal solution - vector<Ipopt::Number> x_sol_; - /// Activities of constraint g( x_sol_) - vector<Ipopt::Number> g_sol_; - /** Dual multipliers of constraints and bounds*/ - vector<Ipopt::Number> duals_sol_; - /** @} */ - - /** Access number of entries in tminlp_ hessian*/ - Ipopt::Index nnz_h_lag() const{ - return nnz_h_lag_;} - /** Access number of entries in tminlp_ hessian*/ - Ipopt::Index nnz_jac_g() const{ - return nnz_jac_g_;} - - /** Acces index_style.*/ - TNLP::IndexStyleEnum index_style() const{ - return index_style_;} - private: - /**@name Default Compiler Generated Methods - * (Hidden to avoid implicit creation/calling). - * These methods are not implemented and - * we do not want the compiler to implement - * them for us, so we declare them private - * and do not define them. This ensures that - * they will not be implicitly created/called. */ - //@{ - /** Default Constructor */ - TMINLP2TNLP(); - - /** Overloaded Equals Operator */ - TMINLP2TNLP& operator=(const TMINLP2TNLP&); - //@} - - /** pointer to the tminlp that is being adapted */ - Ipopt::SmartPtr<TMINLP> tminlp_; - - /** @name Internal copies of data allowing caller to modify the MINLP */ - //@{ - /// Number of non-zeroes in the constraints jacobian. - Ipopt::Index nnz_jac_g_; - /// Number of non-zeroes in the lagrangian hessian - Ipopt::Index nnz_h_lag_; - /**index style (fortran or C)*/ - TNLP::IndexStyleEnum index_style_; - - /** Return status of the optimization process*/ - Ipopt::SolverReturn return_status_; - /** Value of the optimal solution found by Ipopt */ - Ipopt::Number obj_value_; - //@} - - /** @name Warmstart object and related data */ - //@{ - /** Pointer to object that holds warmstart information */ - Ipopt::SmartPtr<IpoptInteriorWarmStarter> curr_warm_starter_; - /** Value for a lower bound that denotes -infinity */ - Ipopt::Number nlp_lower_bound_inf_; - /** Value for a upper bound that denotes infinity */ - Ipopt::Number nlp_upper_bound_inf_; - /** Option from Ipopt - we currently use it to see if we want to - * use some clever warm start or just the last iterate from the - * previous run */ - bool warm_start_entire_iterate_; - /** Do we need a new warm starter object */ - bool need_new_warm_starter_; - //@} - - - /** Private method that throws an exception if the variable bounds - * are not consistent with the variable type */ - void throw_exception_on_bad_variable_bound(Ipopt::Index i); - - private: - // Delete all arrays - void gutsOfDelete(); - - /** Copies all the arrays. - \warning this and other should be two instances of the same problem - \warning AW: I am trying to mimic a copy construction for Cbc - use with great care not safe. - */ - void gutsOfCopy(const TMINLP2TNLP &source); - }; - -} // namespace Ipopt - -#endif |