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diff --git a/newstructure/thirdparty/linux/include/coin/BonOsiTMINLPInterface.hpp b/newstructure/thirdparty/linux/include/coin/BonOsiTMINLPInterface.hpp new file mode 100644 index 0000000..3d95545 --- /dev/null +++ b/newstructure/thirdparty/linux/include/coin/BonOsiTMINLPInterface.hpp @@ -0,0 +1,1342 @@ +// (C) Copyright International Business Machines Corporation, Carnegie Mellon University 2004, 2007 +// 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 OsiTMINLPInterface_H +#define OsiTMINLPInterface_H + +#define INT_BIAS 0e-8 + +#include <string> +#include <iostream> + +#include "OsiSolverInterface.hpp" +#include "CoinWarmStartBasis.hpp" + +#include "BonCutStrengthener.hpp" +//#include "BonRegisteredOptions.hpp" + +namespace Bonmin { + class TMINLP; + class TMINLP2TNLP; + class TMINLP2OsiLP; + class TNLP2FPNLP; + class TNLPSolver; + class RegisteredOptions; + class StrongBranchingSolver; + + /** Solvers for solving nonlinear programs.*/ + enum Solver{ + EIpopt=0 /** <a href="http://projects.coin-or.org/Ipopt"> Ipopt </a> interior point algorithm.*/, + EFilterSQP /** <a href="http://www-unix.mcs.anl.gov/~leyffer/solvers.html"> filterSQP </a> Sequential Quadratic Programming algorithm.*/, + EAll/** Use all solvers.*/ + }; +/** + This is class provides an Osi interface for a Mixed Integer Linear Program + expressed as a TMINLP + (so that we can use it for example as the continuous solver in Cbc). +*/ + +class OsiTMINLPInterface : public OsiSolverInterface +{ + friend class BonminParam; + +public: + + //############################################################################# + + /**Error class to throw exceptions from OsiTMINLPInterface. + * Inherited from CoinError, we just want to have a different class to be able to catch + * errors thrown by OsiTMINLPInterface. + */ +class SimpleError : public CoinError + { + private: + SimpleError(); + + public: + ///Alternate constructor using strings + SimpleError(std::string message, + std::string methodName, + std::string f = std::string(), + int l = -1) + : + CoinError(message,methodName,std::string("OsiTMINLPInterface"), f, l) + {} + } + ; + +#ifdef __LINE__ +#define SimpleError(x, y) SimpleError((x), (y), __FILE__, __LINE__) +#endif + + // Error when problem is not solved + TNLPSolver::UnsolvedError * newUnsolvedError(int num, Ipopt::SmartPtr<TMINLP2TNLP> problem, std::string name){ + return app_->newUnsolvedError(num, problem, name); + } + //############################################################################# + + enum WarmStartModes{ + None, + FakeBasis, + Optimum, + InteriorPoint}; + + /** Type of the messages specifically written by OsiTMINLPInterface.*/ + enum MessagesTypes{ + SOLUTION_FOUND/**found a feasible solution*/, + INFEASIBLE_SOLUTION_FOUND/**found an infeasible problem*/, + UNSOLVED_PROBLEM_FOUND/**found an unsolved problem*/, + WARNING_RESOLVING /** Warn that a problem is resolved*/, + WARN_SUCCESS_WS/** Problem not solved with warm start but solved without*/, + WARN_SUCCESS_RANDOM/** Subproblem not solve with warm start but solved with random point*/, + WARN_CONTINUING_ON_FAILURE/** a failure occured but is continuing*/, + SUSPECT_PROBLEM/** Output the number of the problem.*/, + SUSPECT_PROBLEM2/** Output the number of the problem.*/, + IPOPT_SUMMARY /** Output summary statistics on Ipopt solution.*/, + BETTER_SOL /** Found a better solution with random values.*/, + LOG_HEAD/** Head of "civilized" log.*/, + LOG_FIRST_LINE/** First line (first solve) of log.*/, + LOG_LINE/**standard line (retry solving) of log.*/, + ALTERNATE_OBJECTIVE/** Recomputed integer feasible with alternate objective function*/, + WARN_RESOLVE_BEFORE_INITIAL_SOLVE /** resolve() has been called but there + was no previous call to initialSolve(). + */, + ERROR_NO_TNLPSOLVER /** Trying to access non-existent TNLPSolver*/, + WARNING_NON_CONVEX_OA /** Warn that there are equality or ranged constraints and OA may works bad.*/, + SOLVER_DISAGREE_STATUS /** Different solver gives different status for problem.*/, + SOLVER_DISAGREE_VALUE /** Different solver gives different optimal value for problem.*/, + OSITMINLPINTERFACE_DUMMY_END + }; + + //############################################################################# + + + /** Messages written by an OsiTMINLPInterface. */ +class Messages : public CoinMessages + { + public: + /// Constructor + Messages(); + }; + + + //############################################################################# + + + /**@name Constructors and destructors */ + //@{ + /// Default Constructor + OsiTMINLPInterface(); + + /** Facilitator to initialize interface. */ + void initialize(Ipopt::SmartPtr<Bonmin::RegisteredOptions> roptions, + Ipopt::SmartPtr<Ipopt::OptionsList> options, + Ipopt::SmartPtr<Ipopt::Journalist> journalist, + const std::string & prefix, + Ipopt::SmartPtr<TMINLP> tminlp); + + /** Facilitator to initialize interface. */ + void initialize(Ipopt::SmartPtr<Bonmin::RegisteredOptions> roptions, + Ipopt::SmartPtr<Ipopt::OptionsList> options, + Ipopt::SmartPtr<Ipopt::Journalist> journalist, + Ipopt::SmartPtr<TMINLP> tminlp){ + initialize(roptions, options, journalist, "bonmin.", tminlp); + } + + /** Set the model to be solved by interface.*/ + void setModel(Ipopt::SmartPtr<TMINLP> tminlp); + /** Set the solver to be used by interface.*/ + void setSolver(Ipopt::SmartPtr<TNLPSolver> app); + /** Sets the TMINLP2TNLP to be used by the interface.*/ + void use(Ipopt::SmartPtr<TMINLP2TNLP> tminlp2tnlp); + /** Copy constructor + */ + OsiTMINLPInterface (const OsiTMINLPInterface &); + + /** Virtual copy constructor */ + OsiSolverInterface * clone(bool copyData = true) const; + + /// Assignment operator + OsiTMINLPInterface & operator=(const OsiTMINLPInterface& rhs); + + /// Destructor + virtual ~OsiTMINLPInterface (); + + + /// Read parameter file + void readOptionFile(const std::string & fileName); + + /// Retrieve OsiTMINLPApplication option list + const Ipopt::SmartPtr<Ipopt::OptionsList> options() const; + /// Retrieve OsiTMINLPApplication option list + Ipopt::SmartPtr<Ipopt::OptionsList> options(); + + const char * prefix() const{ + if(!IsValid(app_)) { + messageHandler()->message(ERROR_NO_TNLPSOLVER, messages_)<<CoinMessageEol; + return NULL; + } + else + return app_->prefix(); + } + //@} + //--------------------------------------------------------------------------- + /**@name Solve methods */ + //@{ + /// Solve initial continuous relaxation + virtual void initialSolve(); + + /// Solve initial continuous relaxation (precising from where) + virtual void initialSolve(const char * whereFrom); + + /** Resolve the continuous relaxation after problem modification. + initialSolve may or may not have been called before this is called. In + any case, this must solve the problem, and speed the process up if it + can reuse any remnants of data that might exist from a previous solve. + */ + virtual void resolve(); + + /** Resolve the continuous relaxation after problem modification. + initialSolve may or may not have been called before this is called. In + any case, this must solve the problem, and speed the process up if it + can reuse any remnants of data that might exist from a previous solve. + */ + virtual void resolve(const char * whereFrom); + + /** Resolve the problem with different random starting points to try to find + a better solution (only makes sense for a non-convex problem.*/ + virtual void resolveForCost(int numretry, bool keepWs); + + /** Method to be called when a problem has failed to be solved. Will try + to resolve it with different settings. + */ + virtual void resolveForRobustness(int numretry); + + /// Nescessary for compatibility with OsiSolverInterface but does nothing. + virtual void branchAndBound() + { + throw SimpleError("Function not implemented for OsiTMINLPInterface","branchAndBound()"); + } + //@} + + + + //--------------------------------------------------------------------------- + ///@name Methods returning info on how the solution process terminated + //@{ + /// Are there a numerical difficulties? + virtual bool isAbandoned() const; + /// Is optimality proven? + virtual bool isProvenOptimal() const; + /// Is primal infeasiblity proven? + virtual bool isProvenPrimalInfeasible() const; + /// Is dual infeasiblity proven? + virtual bool isProvenDualInfeasible() const; + /// Is the given primal objective limit reached? + virtual bool isPrimalObjectiveLimitReached() const; + /// Is the given dual objective limit reached? + virtual bool isDualObjectiveLimitReached() const; + /// Iteration limit reached? + virtual bool isIterationLimitReached() const; + + ///Warn solver that branch-and-bound is continuing after a failure + void continuingOnAFailure() + { + hasContinuedAfterNlpFailure_ = true; + } + + + //Added by Claudia + + double getNewCutoffDecr() + { + return newCutoffDecr; + } + + void setNewCutoffDecr(double d) + { + newCutoffDecr = d; + } + + + /// Did we continue on a failure + bool hasContinuedOnAFailure() + { + return hasContinuedAfterNlpFailure_; + } + /// tell to ignore the failures (don't throw, don't fathom, don't report) + void ignoreFailures() + { + pretendFailIsInfeasible_ = 2; + } + /// Force current solution to be infeasible + void forceInfeasible() + { + problem_->set_obj_value(1e200); + } + /// Force current solution to be branched on (make it fractionnal with small objective) + void forceBranchable() + { + problem_->set_obj_value(-1e200); + problem_->force_fractionnal_sol(); + } + //@} + + + //--------------------------------------------------------------------------- + /**@name Parameter set/get methods + + The set methods return true if the parameter was set to the given value, + false otherwise. There can be various reasons for failure: the given + parameter is not applicable for the solver (e.g., refactorization + frequency for the clp algorithm), the parameter is not yet implemented + for the solver or simply the value of the parameter is out of the range + the solver accepts. If a parameter setting call returns false check the + details of your solver. + + The get methods return true if the given parameter is applicable for the + solver and is implemented. In this case the value of the parameter is + returned in the second argument. Otherwise they return false. + */ + //@{ + // Set an integer parameter + bool setIntParam(OsiIntParam key, int value); + // Set an double parameter + bool setDblParam(OsiDblParam key, double value); + // Set a string parameter + bool setStrParam(OsiStrParam key, const std::string & value); + // Get an integer parameter + bool getIntParam(OsiIntParam key, int& value) const; + // Get an double parameter + bool getDblParam(OsiDblParam key, double& value) const; + // Get a string parameter + bool getStrParam(OsiStrParam key, std::string& value) const; + + // Get the push values for starting point + inline double getPushFact() const + { + return pushValue_; + } + + //@} + + + //--------------------------------------------------------------------------- + /**@name Problem information methods + + These methods call the solver's query routines to return + information about the problem referred to by the current object. + Querying a problem that has no data associated with it result in + zeros for the number of rows and columns, and NULL pointers from + the methods that return vectors. + + Const pointers returned from any data-query method are valid as + long as the data is unchanged and the solver is not called. + */ + //@{ + /// Get number of columns + virtual int getNumCols() const; + + /// Get number of rows + virtual int getNumRows() const; + + ///get name of variables + const OsiSolverInterface::OsiNameVec& getVarNames() ; + /// Get pointer to array[getNumCols()] of column lower bounds + virtual const double * getColLower() const; + + /// Get pointer to array[getNumCols()] of column upper bounds + virtual const double * getColUpper() const; + + /** Get pointer to array[getNumRows()] of row constraint senses. + <ul> + <li>'L': <= constraint + <li>'E': = constraint + <li>'G': >= constraint + <li>'R': ranged constraint + <li>'N': free constraint + </ul> + */ + virtual const char * getRowSense() const; + + /** Get pointer to array[getNumRows()] of rows right-hand sides + <ul> + <li> if rowsense()[i] == 'L' then rhs()[i] == rowupper()[i] + <li> if rowsense()[i] == 'G' then rhs()[i] == rowlower()[i] + <li> if rowsense()[i] == 'R' then rhs()[i] == rowupper()[i] + <li> if rowsense()[i] == 'N' then rhs()[i] == 0.0 + </ul> + */ + virtual const double * getRightHandSide() const; + + /** Get pointer to array[getNumRows()] of row ranges. + <ul> + <li> if rowsense()[i] == 'R' then + rowrange()[i] == rowupper()[i] - rowlower()[i] + <li> if rowsense()[i] != 'R' then + rowrange()[i] is 0.0 + </ul> + */ + virtual const double * getRowRange() const; + + /// Get pointer to array[getNumRows()] of row lower bounds + virtual const double * getRowLower() const; + + /// Get pointer to array[getNumRows()] of row upper bounds + virtual const double * getRowUpper() const; + + /** Get objective function sense (1 for min (default), -1 for max) + * Always minimizes */ + virtual double getObjSense() const + { + return 1; + } + + /// Return true if column is continuous + virtual bool isContinuous(int colNumber) const; + + /// Return true if column is binary + virtual bool isBinary(int columnNumber) const; + + /** Return true if column is integer. + Note: This function returns true if the the column + is binary or a general integer. + */ + virtual bool isInteger(int columnNumber) const; + + /// Return true if column is general integer + virtual bool isIntegerNonBinary(int columnNumber) const; + + /// Return true if column is binary and not fixed at either bound + virtual bool isFreeBinary(int columnNumber) const; + + /// Get solver's value for infinity + virtual double getInfinity() const; + + ///Get priorities on integer variables. + const int * getPriorities() const + { + const TMINLP::BranchingInfo * branch = tminlp_->branchingInfo(); + if(branch) + return branch->priorities; + else return NULL; + } + ///get prefered branching directions + const int * getBranchingDirections() const + { + const TMINLP::BranchingInfo * branch = tminlp_->branchingInfo(); + if(branch) + return branch->branchingDirections; + else return NULL; + } + const double * getUpPsCosts() const + { + const TMINLP::BranchingInfo * branch = tminlp_->branchingInfo(); + if(branch) + return branch->upPsCosts; + else return NULL; + } + const double * getDownPsCosts() const + { + const TMINLP::BranchingInfo * branch = tminlp_->branchingInfo(); + if(branch) + return branch->downPsCosts; + else return NULL; + } + + + //@} + + /**@name Methods related to querying the solution */ + //@{ + /// Get pointer to array[getNumCols()] of primal solution vector + virtual const double * getColSolution() const; + + /// Get pointer to array[getNumRows()] of dual prices + virtual const double * getRowPrice() const; + + /// Get a pointer to array[getNumCols()] of reduced costs + virtual const double * getReducedCost() const; + + /** Get pointer to array[getNumRows()] of row activity levels (constraint + matrix times the solution vector */ + virtual const double * getRowActivity() const; + + + /** Get how many iterations it took to solve the problem (whatever + "iteration" mean to the solver. + * \todo Figure out what it could mean for Ipopt. + */ + virtual int getIterationCount() const; + + /** get total number of calls to solve.*/ + int nCallOptimizeTNLP() + { + return nCallOptimizeTNLP_; + } + /** get total time taken to solve NLP's. */ + double totalNlpSolveTime() + { + return totalNlpSolveTime_; + } + /** get total number of iterations */ + int totalIterations() + { + return totalIterations_; + } + + + //@} + //------------------------------------------------------------------------- + /**@name Methods to modify the objective, bounds, and solution + */ + //@{ + + /** Set a single column lower bound. + Use -getInfinity() for -infinity. */ + virtual void setColLower( int elementIndex, double elementValue ); + + /** Set a single column upper bound. + Use getInfinity() for infinity. */ + virtual void setColUpper( int elementIndex, double elementValue ); + + /** Set the lower bounds for all columns + array [getNumCols()] is an array of values for the objective. + */ + virtual void setColLower(const double * array); + + /** Set the upper bounds for all columns + array [getNumCols()] is an array of values for the objective. + */ + virtual void setColUpper(const double * array); + + + /** Set a single row lower bound. + Use -getInfinity() for -infinity. */ + virtual void setRowLower( int elementIndex, double elementValue ); + + /** Set a single row upper bound. + Use getInfinity() for infinity. */ + virtual void setRowUpper( int elementIndex, double elementValue ); + + /** Set the type of a single row */ + virtual void setRowType(int index, char sense, double rightHandSide, + double range); + + + /** \brief Set the objective function sense (disabled). + * (1 for min (default), -1 for max) + \todo Make it work. + \bug Can not treat maximisation problems. */ + virtual void setObjSense(double s); + + /** Set the primal solution variable values + Set the values for the starting point. + \warning getColSolution will never return this vector (unless it is optimal). + */ + virtual void setColSolution(const double *colsol); + + /** Set dual solution variable values. + set the values for the starting point. + \warning getRowPrice will never return this vector (unless it is optimal). + */ + virtual void setRowPrice(const double * rowprice); + + //@} + + + //--------------------------------------------------------------------------- + /**@name WarmStart related methods (those should really do nothing for the moment)*/ + //@{ + + /*! \brief Get an empty warm start object + + This routine returns an empty CoinWarmStartBasis object. Its purpose is + to provide a way to give a client a warm start basis object of the + appropriate type, which can resized and modified as desired. + */ + virtual CoinWarmStart *getEmptyWarmStart () const; + + /** Get warmstarting information */ + virtual CoinWarmStart* getWarmStart() const; + + /** Set warmstarting information. Return true/false depending on whether + the warmstart information was accepted or not. */ + virtual bool setWarmStart(const CoinWarmStart* warmstart); + + void setWarmStartMode(int mode) { + warmStartMode_ = (WarmStartModes) mode; + } + WarmStartModes getWarmStartMode() { + return warmStartMode_; + } + + void randomStartingPoint(); + + //Returns true if a basis is available + virtual bool basisIsAvailable() const + { + // Throw an exception + throw SimpleError("Needs coding for this interface", "basisIsAvailable"); + } + + + //@} + + //------------------------------------------------------------------------- + /**@name Methods to set variable type */ + //@{ + /** Set the index-th variable to be a continuous variable */ + virtual void setContinuous(int index); + /** Set the index-th variable to be an integer variable */ + virtual void setInteger(int index); + //@} + + //Set numIterationSuspect_ + void setNumIterationSuspect(int value) + { + numIterationSuspect_ = value; + } + + /**@name Dummy functions + * Functions which have to be implemented in an OsiSolverInterface, + * but which do not do anything (but throwing exceptions) here in the case of a + * minlp solved using an nlp solver for continuous relaxations */ + //@{ + + /** Cbc will understand that no matrix exsits if return -1 + */ + virtual int getNumElements() const + { + return -1; + } + + + /** This returns the objective function gradient at the current + * point. It seems to be required for Cbc's pseudo cost + * initialization + */ + virtual const double * getObjCoefficients() const; + + /** We have to keep this but it will return NULL. + */ + virtual const CoinPackedMatrix * getMatrixByRow() const + { + return NULL; + } + + + /** We have to keep this but it will return NULL. + */ + virtual const CoinPackedMatrix * getMatrixByCol() const + { + return NULL; + } + + /** We have to keep this but it will throw an error. + */ + virtual void setObjCoeff( int elementIndex, double elementValue ) + { + throw SimpleError("OsiTMINLPInterface does not implement this function.", + "setObjCoeff"); + } + + /** We have to keep this but it will throw an error. + */ + virtual void addCol(const CoinPackedVectorBase& vec, + const double collb, const double colub, + const double obj) + { + throw SimpleError("OsiTMINLPInterface does not implement this function.", + "addCol"); + } + /** We have to keep this but it will throw an error. + */ + virtual void deleteCols(const int num, const int * colIndices) + { + throw SimpleError("OsiTMINLPInterface does not implement this function.", + "deleteCols"); + } + + /** We have to keep this but it will throw an error. + */ + virtual void addRow(const CoinPackedVectorBase& vec, + const double rowlb, const double rowub) + { + throw SimpleError("OsiTMINLPInterface does not implement this function.", + "addRow"); + } + /** We have to keep this but it will throw an error. + */ + virtual void addRow(const CoinPackedVectorBase& vec, + const char rowsen, const double rowrhs, + const double rowrng) + { + throw SimpleError("OsiTMINLPInterface model does not implement this function.", + "addRow"); + } + /** We have to keep this but it will throw an error. + */ + virtual void deleteRows(const int num, const int * rowIndices) + { + if(num) + freeCachedRowRim(); + problem_->removeCuts(num, rowIndices); + } + + + /** We have to keep this but it will throw an error + */ + virtual void loadProblem(const CoinPackedMatrix& matrix, + const double* collb, const double* colub, + const double* obj, + const double* rowlb, const double* rowub) + { + throw SimpleError("OsiTMINLPInterface does not implement this function.", + "loadProblem"); + } + + + /** We have to keep this but it will throw an error. + */ + virtual void assignProblem(CoinPackedMatrix*& matrix, + double*& collb, double*& colub, double*& obj, + double*& rowlb, double*& rowub) + { + throw SimpleError("OsiTMINLPInterface does not implement this function.", + "assignProblem"); + } + + /** We have to keep this but it will throw an error. + */ + virtual void loadProblem(const CoinPackedMatrix& matrix, + const double* collb, const double* colub, + const double* obj, + const char* rowsen, const double* rowrhs, + const double* rowrng) + { + throw SimpleError("OsiTMINLPInterface does not implement this function.", + "loadProblem"); + } + + /** We have to keep this but it will throw an error. + */ + virtual void assignProblem(CoinPackedMatrix*& matrix, + double*& collb, double*& colub, double*& obj, + char*& rowsen, double*& rowrhs, + double*& rowrng) + { + throw SimpleError("OsiTMINLPInterface does not implement this function.", + "assignProblem"); + } + + + /** We have to keep this but it will throw an error. + */ + virtual void loadProblem(const int numcols, const int numrows, + const int* start, const int* index, + const double* value, + const double* collb, const double* colub, + const double* obj, + const double* rowlb, const double* rowub) + { + throw SimpleError("OsiTMINLPInterface does not implement this function.", + "loadProblem"); + } + + /** We have to keep this but it will throw an error. + */ + virtual void loadProblem(const int numcols, const int numrows, + const int* start, const int* index, + const double* value, + const double* collb, const double* colub, + const double* obj, + const char* rowsen, const double* rowrhs, + const double* rowrng) + { + throw SimpleError("OsiTMINLPInterface model does not implement this function.", + "loadProblem"); + } + + /** We have to keep this but it will throw an error. + */ + virtual int readMps(const char *filename, + const char *extension = "mps") + { + throw SimpleError("OsiTMINLPInterface does not implement this function.", + "readMps"); + } + + + /** We have to keep this but it will throw an error. + */ + virtual void writeMps(const char *filename, + const char *extension = "mps", + double objSense=0.0) const + { + throw SimpleError("OsiTMINLPInterface does not implement this function.", + "writeMps"); + } + + /** Throws an error */ + virtual std::vector<double*> getDualRays(int maxNumRays, bool fullRay = false) const + { + throw SimpleError("OsiTMINLPInterface does not implement this function.", + "getDualRays"); + } + + /** Throws an error */ + virtual std::vector<double*> getPrimalRays(int maxNumRays) const + { + throw SimpleError("OsiTMINLPInterface does not implement this function.", + "getPrimalRays"); + } + + //@} + + + + //--------------------------------------------------------------------------- + + + + /**@name Control of Ipopt output + */ + //@{ + void setSolverOutputToDefault(){ + app_->setOutputToDefault();} + void forceSolverOutput(int log_level){ + app_->forceSolverOutput(log_level);} + //@} + + /**@name Sets and Getss */ + //@{ + /// Get objective function value (can't use default) + virtual double getObjValue() const; + + //@} + + /** get pointer to the TMINLP2TNLP adapter */ + const TMINLP2TNLP * problem() const + { + return GetRawPtr(problem_); + } + + TMINLP2TNLP * problem() + { + return GetRawPtr(problem_); + } + + const TMINLP * model() const + { + return GetRawPtr(tminlp_); + } + + Bonmin::TMINLP * model() + { + return GetRawPtr(tminlp_); + } + + const Bonmin::TNLPSolver * solver() const + { + return GetRawPtr(app_); + } + + const std::list<Ipopt::SmartPtr<TNLPSolver> >& debug_apps() const{ + return debug_apps_; + } + + TNLPSolver * solver() + { + return GetRawPtr(app_); + } + /** \name Methods to build outer approximations */ + //@{ + /** \name Methods to build outer approximations */ + //@{ + /** \brief Extract a linear relaxation of the MINLP. + * Use user-provided point to build first-order outer-approximation constraints at the optimum. + * And put it in an OsiSolverInterface. + */ + virtual void extractLinearRelaxation(OsiSolverInterface &si, const double *x, + bool getObj = 1); + + /** Add constraint corresponding to objective function.*/ + virtual void addObjectiveFunction(OsiSolverInterface &si, const double * x); +#if 1 + /** \brief Extract a linear relaxation of the MINLP. + * Solve the continuous relaxation and takes first-order outer-approximation constraints at the optimum. + * The put everything in an OsiSolverInterface. + */ + virtual void extractLinearRelaxation(OsiSolverInterface &si, bool getObj = 1, + bool solveNlp = 1){ + if(solveNlp) + initialSolve("build initial OA"); + extractLinearRelaxation(si, getColSolution(), getObj); + if(solveNlp){ + app_->enableWarmStart(); + setColSolution(problem()->x_sol()); + setRowPrice(problem()->duals_sol()); + } + } +#endif + /** Get the outer approximation constraints at the current optimal point. + If x2 is different from NULL only add cuts violated by x2. + (Only get outer-approximations of nonlinear constraints of the problem.)*/ + void getOuterApproximation(OsiCuts &cs, int getObj, const double * x2, bool global) +{ + getOuterApproximation(cs, getColSolution(), getObj, x2, global); +} + + /** Get the outer approximation constraints at provided point. + If x2 is different from NULL only add cuts violated by x2. + (Only get outer-approximations of nonlinear constraints of the problem.)*/ + void getOuterApproximation(OsiCuts &cs, const double * x, int getObj, const double * x2, bool global){ + getOuterApproximation(cs, x, getObj, x2, 0., global);} + + /** Get the outer approximation constraints at provided point. + If x2 is different from NULL only add cuts violated by x2 by more than delta. + (Only get outer-approximations of nonlinear constraints of the problem.)*/ + virtual void getOuterApproximation(OsiCuts &cs, const double * x, int getObj, const double * x2, + double theta, bool global); + + /** Get the outer approximation at provided point for given constraint. */ + virtual void getConstraintOuterApproximation(OsiCuts & cs, int constraintNumber, + const double * x, + const double * x2, bool global); + + /** Get the outer approximation at current optimal point for given constraint. */ + void getConstraintOuterApproximation(OsiCuts & cs, int constraintNumber, + const double * x2, bool global){ + getConstraintOuterApproximation(cs, constraintNumber, getColSolution(),x2,global); + } + + +/** Get a benders cut from solution.*/ +void getBendersCut(OsiCuts &cs, bool global); + + /** Given a point x_bar this solves the problem of finding the point which minimize a convex + *combination between the distance to x_bar and the original objective function f(x): + * \f$ min a * (\sum\limits_{i=1}^n ||x_{ind[i]} -\overline{x}_i)||_L) + (1 - a)* s *f(x) \f$ + * \return Distance between feasibility set a x_bar on components in ind + * \param n number of elements in array x_bar and ind + * \param s scaling of the original objective. + * \param a Combination to take between feasibility and original objective (must be between 0 and 1). + * \param L L-norm to use (can be either 1 or 2). + */ + double solveFeasibilityProblem(size_t n, const double * x_bar, const int* ind, double a, double s, int L); + + /** Given a point x_bar this solves the problem of finding the point which minimize + * the distance to x_bar while satisfying the additional cutoff constraint: + * \f$ min \sum\limits_{i=1}^n ||x_{ind[i]} -\overline{x}_i)||_L$ + * \return Distance between feasibility set a x_bar on components in ind + * \param n number of elements in array x_bar and ind + * \param L L-norm to use (can be either 1 or 2). + * \param cutoff objective function value of a known integer feasible solution + */ + double solveFeasibilityProblem(size_t n, const double * x_bar, const int* ind, int L, double cutoff); + + /** Given a point x_bar setup feasibility problem and switch so that every call to initialSolve or resolve will + solve it.*/ + void switchToFeasibilityProblem(size_t n, const double * x_bar, const int* ind, double a, double s, int L); + + /** Given a point x_bar setup feasibility problem and switch so that every call to initialSolve or resolve will + solve it. This is to be used in the local branching heuristic */ + void switchToFeasibilityProblem(size_t n, const double * x_bar, const int* ind, + double rhs_local_branching_constraint); + + /** switch back to solving original problem.*/ + void switchToOriginalProblem(); + + /** round solution and check its feasibility.*/ + void round_and_check(double tolerance, + OsiObject ** objects = 0, int nObjects = -1){ + if(!problem_->check_solution(objects, nObjects)){ + optimizationStatus_ = TNLPSolver::provenInfeasible; + } + } + //@} + + /** \name output for OA cut generation + \todo All OA code here should be moved to a separate class sometime.*/ + //@{ + /** OA Messages types.*/ + enum OaMessagesTypes { + CUT_NOT_VIOLATED_ENOUGH = 0/** Says that one cut has been generarted, where from, which is the violation.*/, + VIOLATED_OA_CUT_GENERATED/** Cut is not violated enough, give violation.*/, + OA_CUT_GENERATED/** Print the cut which has been generated.*/, + OA_MESSAGES_DUMMY_END/** Dummy end.*/}; + /** Class to store OA Messages.*/ + class OaMessages :public CoinMessages{ + public: + /** Default constructor.*/ + OaMessages(); + }; + /** Like a CoinMessageHandler but can print a cut also.*/ + class OaMessageHandler : public CoinMessageHandler{ + public: + /** Default constructor.*/ + OaMessageHandler():CoinMessageHandler(){ + } + /** Constructor to put to file pointer (fp won't be closed).*/ + OaMessageHandler(FILE * fp):CoinMessageHandler(fp){ + } + /** Destructor.*/ + virtual ~OaMessageHandler(){ + } + /** Copy constructor.*/ + OaMessageHandler(const OaMessageHandler &other): + CoinMessageHandler(other){} + /** Constructor from a regular CoinMessageHandler.*/ + OaMessageHandler(const CoinMessageHandler &other): + CoinMessageHandler(other){} + /** Assignment operator.*/ + OaMessageHandler & operator=(const OaMessageHandler &rhs){ + CoinMessageHandler::operator=(rhs); + return *this;} + /** Virtual copy */ + virtual CoinMessageHandler* clone() const{ + return new OaMessageHandler(*this);} + /** print an OsiRowCut.*/ + void print(OsiRowCut &row); + }; + void setOaMessageHandler(const CoinMessageHandler &handler){ + delete oaHandler_; + oaHandler_ = new OaMessageHandler(handler); + } + //@} + + //----------------------------------------------------------------------- + /** Apply a collection of cuts. + */ + virtual ApplyCutsReturnCode applyCuts(const OsiCuts & cs, + double effectivenessLb = 0.0){ + freeCachedRowRim(); + problem_->addCuts(cs); + ApplyCutsReturnCode rc; + return rc;} + + /** Add a collection of linear cuts to problem formulation.*/ + virtual void applyRowCuts(int numberCuts, const OsiRowCut * cuts); + + + /** Add a collection of linear cuts to the problem formulation */ + virtual void applyRowCuts(int numberCuts, const OsiRowCut ** cuts) + { + if(numberCuts) + freeCachedRowRim(); + problem_->addCuts(numberCuts, cuts); + } + + /** Get infinity norm of constraint violation for x. Put into + obj the objective value of x.*/ + double getConstraintsViolation(const double * x, double & obj); + + /** Get infinity norm of constraint violation for x and error in objective + value where obj is the estimated objective value of x.*/ + double getNonLinearitiesViolation(const double *x, const double obj); + +//--------------------------------------------------------------------------- + + void extractInterfaceParams(); + + + /** To set some application specific defaults. */ + virtual void setAppDefaultOptions(Ipopt::SmartPtr<Ipopt::OptionsList> Options); + + /** Register all possible options to Bonmin */ + static void registerOptions (Ipopt::SmartPtr<Bonmin::RegisteredOptions> roptions); + + Ipopt::SmartPtr<Bonmin::RegisteredOptions> regOptions(){ + if(IsValid(app_)) + return app_->roptions(); + else + return NULL; + } + + /** @name Methods related to strong branching */ + //@{ + /// Set the strong branching solver + void SetStrongBrachingSolver(Ipopt::SmartPtr<StrongBranchingSolver> strong_branching_solver); + /// Create a hot start snapshot of the optimization process. In our + /// case, we initialize the StrongBrachingSolver. + virtual void markHotStart(); + /// Optimize starting from the hot start snapshot. In our case, we + /// call the StrongBranchingSolver to give us an approximate + /// solution for the current state of the bounds + virtual void solveFromHotStart(); + /// Delete the hot start snapshot. In our case we deactivate the + /// StrongBrachingSolver. + virtual void unmarkHotStart(); + //@} + + /// Get values of tiny_ and very_tiny_ + void get_tolerances(double &tiny, double&very_tiny, double &rhsRelax, double &infty){ + tiny = tiny_; + very_tiny = veryTiny_; + rhsRelax = rhsRelax_; + infty = infty_; + } + + void set_linearizer(Ipopt::SmartPtr<TMINLP2OsiLP> linearizer); + + Ipopt::SmartPtr<TMINLP2OsiLP> linearizer(); +protected: + + //@} + + enum RandomGenerationType{ + uniform =0, perturb=1, perturb_suffix=2}; + /// Initialize data structures for storing the jacobian + int initializeJacobianArrays(); + + ///@name Virtual callbacks for application specific stuff + //@{ + virtual std::string appName() + { + return "bonmin"; + } + //@} + ///@name Protected methods + //@{ + + /** Call Ipopt to solve or resolve the problem and check for errors.*/ + void solveAndCheckErrors(bool doResolve, bool throwOnFailure, + const char * whereFrom); + + + /** Add a linear cut to the problem formulation. + */ + virtual void applyRowCut( const OsiRowCut & rc ) + { + const OsiRowCut * cut = &rc; + problem_->addCuts(1, &cut); + } + /** We have to keep this but it will throw an error. + */ + virtual void applyColCut( const OsiColCut & cc ) + { + throw SimpleError("Ipopt model does not implement this function.", + "applyColCut"); + } + +// /** Read the name of the variables in an ampl .col file. */ +// void readVarNames() const; + + //@} + + /**@name Model and solver */ + //@{ + /** TMINLP model.*/ + Ipopt::SmartPtr<TMINLP> tminlp_; + /** Adapter for a MINLP to a NLP */ + Ipopt::SmartPtr<TMINLP2TNLP> problem_; + /** Problem currently optimized (may be problem_ or feasibilityProblem_)*/ + Ipopt::SmartPtr<Ipopt::TNLP> problem_to_optimize_; + /** Is true if and only if in feasibility mode.*/ + bool feasibility_mode_; + /** Solver for a TMINLP. */ + Ipopt::SmartPtr<TNLPSolver> app_; + + /** Alternate solvers for TMINLP.*/ + std::list<Ipopt::SmartPtr<TNLPSolver> > debug_apps_; + /** Do we use the other solvers?*/ + bool testOthers_; + //@} + + /** Warmstart information for reoptimization */ + CoinWarmStart* warmstart_; + + /**@name Cached information on the problem */ + //@{ + /** Free cached data relative to variables */ + void freeCachedColRim(); + /** Free cached data relative to constraints */ + void freeCachedRowRim(); + /** Free all cached data*/ + void freeCachedData(); + /** Extract rowsense_ vector rhs_ vector and rowrange_ vector from the lower and upper bounds + * on the constraints */ + void extractSenseRhsAndRange() const; + /// Pointer to dense vector of row sense indicators + mutable char *rowsense_; + + /// Pointer to dense vector of row right-hand side values + mutable double *rhs_; + + /// Pointer to dense vector of slack upper bounds for range constraints (undefined for non-range rows) + mutable double *rowrange_; + /** Pointer to dense vector of reduced costs + \warning Always 0. with Ipopt*/ + mutable double *reducedCosts_; + /** DualObjectiveLimit is used to store the cutoff in Cbc*/ + double OsiDualObjectiveLimit_; + /** does the file variable names exists (will check automatically).*/ + mutable bool hasVarNamesFile_; + //@} + /// number of time NLP has been solved + int nCallOptimizeTNLP_; + /// Total solution time of NLP + double totalNlpSolveTime_; + /// toatal number of iterations + int totalIterations_; + /// max radius for random point + double maxRandomRadius_; + /// Method to pick a random starting point. + int randomGenerationType_; + /// Maximum perturbation value + double max_perturbation_; + /// Ipopt value for pushing initial point inside the bounds + double pushValue_; + /// Number of times problem will be resolved in initialSolve (root node) + int numRetryInitial_; + /// Number of times problem will be resolved in resolve + int numRetryResolve_; + /// Number of times infeasible problem will be resolved. + int numRetryInfeasibles_; + /// Number of times problem will be resolved in case of a failure + int numRetryUnsolved_; + /// If infeasibility for a problem is less than this, let's be carrefull. It might be feasible + double infeasibility_epsilon_; + + + //Added by Claudia + /// Dynamic cutOff_ + int dynamicCutOff_; + /// coeff_var_threshold_ + double coeff_var_threshold_; + /// first_perc_for_cutoff_decr_ + double first_perc_for_cutoff_decr_; + /// second_perc_for_cutoff_decr_ + double second_perc_for_cutoff_decr_; + + + /** Messages specific to an OsiTMINLPInterface. */ + Messages messages_; + /** If not 0 when a problem is not solved (failed to be solved) + will pretend that it is infeasible. If == 1 will care + (i.e. record the fact issue messages to user), if ==2 don't care (somebody else will) */ + int pretendFailIsInfeasible_; + + mutable int pretendSucceededNext_; + + /** did we ever continue optimization ignoring a failure. */ + bool hasContinuedAfterNlpFailure_; + /** number iterations above which a problem is considered suspect (-1 is considered \f$+ \infty \f$). + If in a call to solve a problem takes more than that number of iterations it will be output to files.*/ + int numIterationSuspect_ ; + /** Has problem been optimized since last change (include setColSolution). + If yes getColSolution will return Ipopt point, otherwise will return + initial point.*/ + bool hasBeenOptimized_; + /** A fake objective function (all variables to 1) to please Cbc + pseudo costs initialization. AW: I changed this, it will now be + the objective gradient at current point. */ + mutable double * obj_; + /** flag to say wether options have been printed or not.*/ + static bool hasPrintedOptions; + + /** Adapter for TNLP to a feasibility problem */ + Ipopt::SmartPtr<TNLP2FPNLP> feasibilityProblem_; + + /** Adapter for TMINLP to an Osi LP */ + Ipopt::SmartPtr<TMINLP2OsiLP> linearizer_; + + /** \name Arrays to store Jacobian matrix */ + //@{ + /** Row indices.*/ + int * jRow_; + /** Column indices.*/ + int * jCol_; + /** Values */ + double * jValues_; + /** Number of elements.*/ + int nnz_jac; + //@} + + ///Store the types of the constraints (linear and nonlinear). + Ipopt::TNLP::LinearityType * constTypes_; + /** Number of nonlinear constraint + */ + int nNonLinear_; + /** Value for small non-zero element which we will try to remove cleanly in OA cuts.*/ + double tiny_; + /** Value for small non-zero element which we will take the risk to ignore in OA cuts.*/ + double veryTiny_; + /** Amount by which to relax OA constraints RHSes*/ + double rhsRelax_; + /** Value for infinity. */ + double infty_; + /** status of last optimization. */ + TNLPSolver::ReturnStatus optimizationStatus_; + /** Flag indicating if the warm start methods actually do something.*/ + WarmStartModes warmStartMode_; + /** Is it the first solve (for random starting point at root options).*/ + bool firstSolve_; + /** Object for strengthening cuts */ + Ipopt::SmartPtr<CutStrengthener> cutStrengthener_; + + /** \name output for OA cut generation + \todo All OA code here should be moved to a separate class sometime.*/ + //@{ + /** OA Messages.*/ + OaMessages oaMessages_; + /** OA Message handler. */ + OaMessageHandler * oaHandler_; + //@} + + double newCutoffDecr; +protected: + /** Facilitator to create an application. */ + void createApplication(Ipopt::SmartPtr<Bonmin::RegisteredOptions> roptions, + Ipopt::SmartPtr<Ipopt::OptionsList> options, + Ipopt::SmartPtr<Ipopt::Journalist> journalist, + const std::string & prefix); + ///Constructor without model only for derived classes + OsiTMINLPInterface(Ipopt::SmartPtr<TNLPSolver> app); + + /** Internal set warm start.*/ + bool internal_setWarmStart(const CoinWarmStart* ws); + + /** internal get warm start.*/ + CoinWarmStart* internal_getWarmStart() const; + + /** Procedure that builds a fake basis. Only tries to make basis consistent with constraints activity.*/ + CoinWarmStart* build_fake_basis() const; +private: + + /** solver to be used for all strong branching solves */ + Ipopt::SmartPtr<StrongBranchingSolver> strong_branching_solver_; + /** status of last optimization before hot start was marked. */ + TNLPSolver::ReturnStatus optimizationStatusBeforeHotStart_; +static const char * OPT_SYMB; +static const char * FAILED_SYMB; +static const char * INFEAS_SYMB; +static const char * TIME_SYMB; +static const char * UNBOUND_SYMB; + /** Get status as a char * for log.*/ + const char * statusAsString(TNLPSolver::ReturnStatus r){ + if(r == TNLPSolver::solvedOptimal || r == TNLPSolver::solvedOptimalTol){ + return OPT_SYMB;} + else if(r == TNLPSolver::provenInfeasible){ + return INFEAS_SYMB;} + else if(r == TNLPSolver::unbounded){ + return UNBOUND_SYMB;} + else if(r == TNLPSolver::timeLimit){ + return TIME_SYMB;} + else return FAILED_SYMB; + } + const char * statusAsString(){ + return statusAsString(optimizationStatus_);} +}; +} +#endif |