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author | Georgey | 2017-07-05 11:40:43 +0530 |
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committer | Georgey | 2017-07-05 11:40:43 +0530 |
commit | 938fef4a37a7b7c61b4b6ff74cb4cfd2f100c427 (patch) | |
tree | b343c0ee5609433c80e0de1db8b6886c9126dc2d /thirdparty/linux/include/coin/BonTMINLP2Quad.hpp | |
parent | 5b72577efe080c5294b32d804e4d26351fef30bc (diff) | |
download | FOSSEE-Optimization-toolbox-938fef4a37a7b7c61b4b6ff74cb4cfd2f100c427.tar.gz FOSSEE-Optimization-toolbox-938fef4a37a7b7c61b4b6ff74cb4cfd2f100c427.tar.bz2 FOSSEE-Optimization-toolbox-938fef4a37a7b7c61b4b6ff74cb4cfd2f100c427.zip |
Added linux shared libraries and header files for int and ecos functions
Diffstat (limited to 'thirdparty/linux/include/coin/BonTMINLP2Quad.hpp')
-rw-r--r-- | thirdparty/linux/include/coin/BonTMINLP2Quad.hpp | 191 |
1 files changed, 191 insertions, 0 deletions
diff --git a/thirdparty/linux/include/coin/BonTMINLP2Quad.hpp b/thirdparty/linux/include/coin/BonTMINLP2Quad.hpp new file mode 100644 index 0000000..4d7f0c6 --- /dev/null +++ b/thirdparty/linux/include/coin/BonTMINLP2Quad.hpp @@ -0,0 +1,191 @@ +// (C) Copyright International Business Machines Corporation 2007 +// All Rights Reserved. +// This code is published under the Eclipse Public License. +// +// Authors : +// Pierre Bonami, International Business Machines Corporation +// +// Date : 10/06/2007 + +#ifndef __TMINLPQuad_HPP__ +#define __TMINLPQuad_HPP__ + +#include "BonTMINLP2TNLP.hpp" +#include "BonQuadRow.hpp" + +namespace Bonmin +{ + + + /** This is a derived class fro TMINLP2TNLP to handle adding quadratic cuts. + */ + class TMINLP2TNLPQuadCuts : public Bonmin::TMINLP2TNLP + { + public: + /**@name Constructors/Destructors */ + //@{ + TMINLP2TNLPQuadCuts(const Ipopt::SmartPtr<Bonmin::TMINLP> tminlp +#ifdef WARM_STARTER + , + const OptionsList& options +#endif + ); + + + /** Copy Constructor + * \warning source and copy point to the same tminlp_. + */ + TMINLP2TNLPQuadCuts(const TMINLP2TNLPQuadCuts&); + + /** Virtual copy.*/ + virtual Bonmin::TMINLP2TNLP * clone() const{ + printf("Cloning TMINLP2TNLPQuadCuts.\n"); + return new TMINLP2TNLPQuadCuts(*this);} + + /** Destructor */ + virtual ~TMINLP2TNLPQuadCuts(); + //@} + /**@name methods to gather information about the NLP */ + //@{ + /** This call is just passed onto parent class and add number of quadratic + cuts*/ + 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); + + /** This call is just passed onto parent class and add bounds of quadratic + cuts*/ + 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); + + virtual bool get_constraints_linearity(Ipopt::Index m, Ipopt::TNLP::LinearityType* const_types); + + /** This call is just passed onto parent class and add + lambda for quadratic cuts*/ + 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 (passed to parent all quadratic + not scaled). + */ + 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); + + + /** 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 (appends constraint values for quadratics).*/ + 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 Cuts management. */ + //@{ + + + /** Add some linear or quadratic cuts to the problem formulation + if some of the OsiRowCuts are quadratic they will be well understood as long as safe is true.*/ + void addCuts(const Cuts& cuts, bool safe); + + + /** Add some cuts to the problem formulaiton (handles Quadratics).*/ + void addCuts(const OsiCuts &cuts); + + /** Add some linear cuts to the problem formulation.*/ + virtual void addCuts(unsigned int numberCuts, const OsiRowCut ** cuts); + + + /** Remove some cuts from the formulation */ + void removeCuts(unsigned int number ,const int * toRemove); + + //@} + // + /** Change objective to a linear one whith given objective function.*/ + void set_linear_objective(int n_var, const double * obj, double c_0); + + /** Reset objective to original one */ + void reset_objective(){ + obj_.clear(); + } + + protected: + /** Add some cuts to the problem formulaiton (handles Quadratics).*/ + void addRowCuts(const OsiCuts &cuts, bool safe); + /**@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 */ + TMINLP2TNLPQuadCuts(); + + /** Overloaded Equals Operator */ + TMINLP2TNLPQuadCuts& operator=(const TMINLP2TNLP&); + //@} + + private: + /** Some storage for quadratic cuts.*/ + vector<QuadRow *> quadRows_; + + /** Storage for the original hessian of the problem.*/ + AdjustableMat H_; + + /** print H_ for debug.*/ + void printH(); + /** Current umber of entries in the jacobian.*/ + int curr_nnz_jac_; + + /** Store user passed linear objective.*/ + vector<double> obj_; + /** constant term in objective function.*/ + double c_; + }; + +} // namespace Ipopt + +#endif + |