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Diffstat (limited to 'thirdparty/windows/include/coin/IpTNLP.hpp')
| -rw-r--r-- | thirdparty/windows/include/coin/IpTNLP.hpp | 580 |
1 files changed, 301 insertions, 279 deletions
diff --git a/thirdparty/windows/include/coin/IpTNLP.hpp b/thirdparty/windows/include/coin/IpTNLP.hpp index c97ba88..b00325c 100644 --- a/thirdparty/windows/include/coin/IpTNLP.hpp +++ b/thirdparty/windows/include/coin/IpTNLP.hpp @@ -1,279 +1,301 @@ -// Copyright (C) 2004, 2009 International Business Machines and others. -// All Rights Reserved. -// This code is published under the Common Public License. -// -// $Id: IpTNLP.hpp 1462 2009-06-02 04:17:13Z andreasw $ -// -// Authors: Carl Laird, Andreas Waechter IBM 2004-08-13 - -#ifndef __IPTNLP_HPP__ -#define __IPTNLP_HPP__ - -#include "IpUtils.hpp" -#include "IpReferenced.hpp" -#include "IpException.hpp" -#include "IpAlgTypes.hpp" -#include "IpReturnCodes.hpp" - -#include <map> - -namespace Ipopt -{ - // forward declarations - class IpoptData; - class IpoptCalculatedQuantities; - class IteratesVector; - - /** Base class for all NLP's that use standard triplet matrix form - * and dense vectors. This is the standard base class for all - * NLP's that use the standard triplet matrix form (as for Harwell - * routines) and dense vectors. The class TNLPAdapter then converts - * this interface to an interface that can be used directly by - * ipopt. - * - * This interface presents the problem form: - * - * min f(x) - * - * s.t. gL <= g(x) <= gU - * - * xL <= x <= xU - * - * In order to specify an equality constraint, set gL_i = gU_i = - * rhs. The value that indicates "infinity" for the bounds - * (i.e. the variable or constraint has no lower bound (-infinity) - * or upper bound (+infinity)) is set through the option - * nlp_lower_bound_inf and nlp_upper_bound_inf. To indicate that a - * variable has no upper or lower bound, set the bound to - * -ipopt_inf or +ipopt_inf respectively - */ - class TNLP : public ReferencedObject - { - public: - /** Type of the constraints*/ - enum LinearityType - { - LINEAR/** Constraint/Variable is linear.*/, - NON_LINEAR/**Constraint/Varaible is non-linear.*/ - }; - - /**@name Constructors/Destructors */ - //@{ - TNLP() - {} - - /** Default destructor */ - virtual ~TNLP() - {} - //@} - - DECLARE_STD_EXCEPTION(INVALID_TNLP); - - /**@name methods to gather information about the NLP */ - //@{ - /** overload this method to return the number of variables - * and constraints, and the number of non-zeros in the jacobian and - * the hessian. The index_style parameter lets you specify C or Fortran - * style indexing for the sparse matrix iRow and jCol parameters. - * C_STYLE is 0-based, and FORTRAN_STYLE is 1-based. - */ - enum IndexStyleEnum { C_STYLE=0, FORTRAN_STYLE=1 }; - virtual bool get_nlp_info(Index& n, Index& m, Index& nnz_jac_g, - Index& nnz_h_lag, IndexStyleEnum& index_style)=0; - - typedef std::map<std::string, std::vector<std::string> > StringMetaDataMapType; - typedef std::map<std::string, std::vector<Index> > IntegerMetaDataMapType; - typedef std::map<std::string, std::vector<Number> > NumericMetaDataMapType; - - /** overload this method to return any meta data for - * the variables and the constraints */ - virtual bool get_var_con_metadata(Index n, - StringMetaDataMapType& var_string_md, - IntegerMetaDataMapType& var_integer_md, - NumericMetaDataMapType& var_numeric_md, - Index m, - StringMetaDataMapType& con_string_md, - IntegerMetaDataMapType& con_integer_md, - NumericMetaDataMapType& con_numeric_md) - - { - return false; - } - - /** overload this method to return the information about the bound - * on the variables and constraints. The value that indicates - * that a bound does not exist is specified in the parameters - * nlp_lower_bound_inf and nlp_upper_bound_inf. By default, - * nlp_lower_bound_inf is -1e19 and nlp_upper_bound_inf is - * 1e19. (see TNLPAdapter) */ - virtual bool get_bounds_info(Index n, Number* x_l, Number* x_u, - Index m, Number* g_l, Number* g_u)=0; - - /** overload this method to return scaling parameters. This is - * only called if the options are set to retrieve user scaling. - * There, use_x_scaling (or use_g_scaling) should get set to true - * only if the variables (or constraints) are to be scaled. This - * method should return true only if the scaling parameters could - * be provided. - */ - 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) - { - return false; - } - - /** overload this method to return the variables linearity - * (TNLP::Linear or TNLP::NonLinear). The var_types - * array should be allocated with length at least n. (default implementation - * just return false and does not fill the array).*/ - virtual bool get_variables_linearity(Index n, LinearityType* var_types) - { - return false; - } - - /** overload this method to return the constraint linearity. - * array should be alocated with length at least n. (default implementation - * just return false and does not fill the array).*/ - virtual bool get_constraints_linearity(Index m, LinearityType* const_types) - { - return false; - } - - /** overload this method to return the starting point. The bool - * variables indicate whether the algorithm wants you to - * initialize x, z_L/z_u, and lambda, respectively. If, for some - * reason, the algorithm wants you to initialize these and you - * cannot, return false, which will cause Ipopt to stop. You - * will have to run Ipopt with different options then. - */ - 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)=0; - - /** overload this method to provide an Ipopt iterate (already in - * the form Ipopt requires it internally) for a warm start. - * Since this is only for expert users, a default dummy - * implementation is provided and returns false. */ - virtual bool get_warm_start_iterate(IteratesVector& warm_start_iterate) - { - return false; - } - - /** overload this method to return the value of the objective function */ - virtual bool eval_f(Index n, const Number* x, bool new_x, - Number& obj_value)=0; - - /** overload this method to return the vector of the gradient of - * the objective w.r.t. x */ - virtual bool eval_grad_f(Index n, const Number* x, bool new_x, - Number* grad_f)=0; - - /** overload this method to return the vector of constraint values */ - virtual bool eval_g(Index n, const Number* x, bool new_x, - Index m, Number* g)=0; - /** overload this method to return 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(Index n, const Number* x, bool new_x, - Index m, Index nele_jac, Index* iRow, - Index *jCol, Number* values)=0; - - /** overload this method to 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. A default implementation is provided, in case the user - * wants to se quasi-Newton approximations to estimate the second - * derivatives and doesn't not neet to implement this method. */ - 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) - { - return false; - } - //@} - - /** @name Solution Methods */ - //@{ - /** This method is called when the algorithm is complete so the TNLP can store/write the solution */ - virtual void finalize_solution(SolverReturn status, - Index n, const Number* x, const Number* z_L, const Number* z_U, - Index m, const Number* g, const Number* lambda, - Number obj_value, - const IpoptData* ip_data, - IpoptCalculatedQuantities* ip_cq)=0; - - /** Intermediate Callback method for the user. Providing dummy - * default implementation. For details see IntermediateCallBack - * in IpNLP.hpp. */ - virtual bool intermediate_callback(AlgorithmMode mode, - Index iter, Number obj_value, - Number inf_pr, Number inf_du, - Number mu, Number d_norm, - Number regularization_size, - Number alpha_du, Number alpha_pr, - Index ls_trials, - const IpoptData* ip_data, - IpoptCalculatedQuantities* ip_cq) - { - return true; - } - //@} - - /** @name Methods for quasi-Newton approximation. If the second - * derivatives are approximated by Ipopt, it is better to do this - * only in the space of nonlinear variables. The following - * methods are call by Ipopt if the quasi-Newton approximation is - * selected. If -1 is returned as number of nonlinear variables, - * Ipopt assumes that all variables are nonlinear. Otherwise, it - * calls get_list_of_nonlinear_variables with an array into which - * the indices of the nonlinear variables should be written - the - * array has the lengths num_nonlin_vars, which is identical with - * the return value of get_number_of_nonlinear_variables(). It - * is assumed that the indices are counted starting with 1 in the - * FORTRAN_STYLE, and 0 for the C_STYLE. */ - //@{ - virtual Index get_number_of_nonlinear_variables() - { - return -1; - } - - virtual bool get_list_of_nonlinear_variables(Index num_nonlin_vars, - Index* pos_nonlin_vars) - { - return false; - } - //@} - - 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 */ - //TNLP(); - - /** Copy Constructor */ - TNLP(const TNLP&); - - /** Overloaded Equals Operator */ - void operator=(const TNLP&); - //@} - }; - -} // namespace Ipopt - -#endif +// Copyright (C) 2004, 2009 International Business Machines and others.
+// All Rights Reserved.
+// This code is published under the Eclipse Public License.
+//
+// $Id: IpTNLP.hpp 2212 2013-04-14 14:51:52Z stefan $
+//
+// Authors: Carl Laird, Andreas Waechter IBM 2004-08-13
+
+#ifndef __IPTNLP_HPP__
+#define __IPTNLP_HPP__
+
+#include "IpUtils.hpp"
+#include "IpReferenced.hpp"
+#include "IpException.hpp"
+#include "IpAlgTypes.hpp"
+#include "IpReturnCodes.hpp"
+
+#include <map>
+
+namespace Ipopt
+{
+ // forward declarations
+ class IpoptData;
+ class IpoptCalculatedQuantities;
+ class IteratesVector;
+
+ /** Base class for all NLP's that use standard triplet matrix form
+ * and dense vectors. This is the standard base class for all
+ * NLP's that use the standard triplet matrix form (as for Harwell
+ * routines) and dense vectors. The class TNLPAdapter then converts
+ * this interface to an interface that can be used directly by
+ * ipopt.
+ *
+ * This interface presents the problem form:
+ *
+ * min f(x)
+ *
+ * s.t. gL <= g(x) <= gU
+ *
+ * xL <= x <= xU
+ *
+ * In order to specify an equality constraint, set gL_i = gU_i =
+ * rhs. The value that indicates "infinity" for the bounds
+ * (i.e. the variable or constraint has no lower bound (-infinity)
+ * or upper bound (+infinity)) is set through the option
+ * nlp_lower_bound_inf and nlp_upper_bound_inf. To indicate that a
+ * variable has no upper or lower bound, set the bound to
+ * -ipopt_inf or +ipopt_inf respectively
+ */
+ class TNLP : public ReferencedObject
+ {
+ public:
+ /** Type of the constraints*/
+ enum LinearityType
+ {
+ LINEAR/** Constraint/Variable is linear.*/,
+ NON_LINEAR/**Constraint/Varaible is non-linear.*/
+ };
+
+ /**@name Constructors/Destructors */
+ //@{
+ TNLP()
+ {}
+
+ /** Default destructor */
+ virtual ~TNLP()
+ {}
+ //@}
+
+ DECLARE_STD_EXCEPTION(INVALID_TNLP);
+
+ /**@name methods to gather information about the NLP */
+ //@{
+ /** overload this method to return the number of variables
+ * and constraints, and the number of non-zeros in the jacobian and
+ * the hessian. The index_style parameter lets you specify C or Fortran
+ * style indexing for the sparse matrix iRow and jCol parameters.
+ * C_STYLE is 0-based, and FORTRAN_STYLE is 1-based.
+ */
+ enum IndexStyleEnum { C_STYLE=0, FORTRAN_STYLE=1 };
+ virtual bool get_nlp_info(Index& n, Index& m, Index& nnz_jac_g,
+ Index& nnz_h_lag, IndexStyleEnum& index_style)=0;
+
+ typedef std::map<std::string, std::vector<std::string> > StringMetaDataMapType;
+ typedef std::map<std::string, std::vector<Index> > IntegerMetaDataMapType;
+ typedef std::map<std::string, std::vector<Number> > NumericMetaDataMapType;
+
+ /** overload this method to return any meta data for
+ * the variables and the constraints */
+ virtual bool get_var_con_metadata(Index n,
+ StringMetaDataMapType& var_string_md,
+ IntegerMetaDataMapType& var_integer_md,
+ NumericMetaDataMapType& var_numeric_md,
+ Index m,
+ StringMetaDataMapType& con_string_md,
+ IntegerMetaDataMapType& con_integer_md,
+ NumericMetaDataMapType& con_numeric_md)
+
+ {
+ return false;
+ }
+
+ /** overload this method to return the information about the bound
+ * on the variables and constraints. The value that indicates
+ * that a bound does not exist is specified in the parameters
+ * nlp_lower_bound_inf and nlp_upper_bound_inf. By default,
+ * nlp_lower_bound_inf is -1e19 and nlp_upper_bound_inf is
+ * 1e19. (see TNLPAdapter) */
+ virtual bool get_bounds_info(Index n, Number* x_l, Number* x_u,
+ Index m, Number* g_l, Number* g_u)=0;
+
+ /** overload this method to return scaling parameters. This is
+ * only called if the options are set to retrieve user scaling.
+ * There, use_x_scaling (or use_g_scaling) should get set to true
+ * only if the variables (or constraints) are to be scaled. This
+ * method should return true only if the scaling parameters could
+ * be provided.
+ */
+ 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)
+ {
+ return false;
+ }
+
+ /** overload this method to return the variables linearity
+ * (TNLP::LINEAR or TNLP::NON_LINEAR). The var_types
+ * array has been allocated with length at least n. (default implementation
+ * just return false and does not fill the array).*/
+ virtual bool get_variables_linearity(Index n, LinearityType* var_types)
+ {
+ return false;
+ }
+
+ /** overload this method to return the constraint linearity.
+ * array has been allocated with length at least n. (default implementation
+ * just return false and does not fill the array).*/
+ virtual bool get_constraints_linearity(Index m, LinearityType* const_types)
+ {
+ return false;
+ }
+
+ /** overload this method to return the starting point. The bool
+ * variables indicate whether the algorithm wants you to
+ * initialize x, z_L/z_u, and lambda, respectively. If, for some
+ * reason, the algorithm wants you to initialize these and you
+ * cannot, return false, which will cause Ipopt to stop. You
+ * will have to run Ipopt with different options then.
+ */
+ 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)=0;
+
+ /** overload this method to provide an Ipopt iterate (already in
+ * the form Ipopt requires it internally) for a warm start.
+ * Since this is only for expert users, a default dummy
+ * implementation is provided and returns false. */
+ virtual bool get_warm_start_iterate(IteratesVector& warm_start_iterate)
+ {
+ return false;
+ }
+
+ /** overload this method to return the value of the objective function */
+ virtual bool eval_f(Index n, const Number* x, bool new_x,
+ Number& obj_value)=0;
+
+ /** overload this method to return the vector of the gradient of
+ * the objective w.r.t. x */
+ virtual bool eval_grad_f(Index n, const Number* x, bool new_x,
+ Number* grad_f)=0;
+
+ /** overload this method to return the vector of constraint values */
+ virtual bool eval_g(Index n, const Number* x, bool new_x,
+ Index m, Number* g)=0;
+ /** overload this method to return 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(Index n, const Number* x, bool new_x,
+ Index m, Index nele_jac, Index* iRow,
+ Index *jCol, Number* values)=0;
+
+ /** overload this method to 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. A default implementation is provided, in case the user
+ * wants to se quasi-Newton approximations to estimate the second
+ * derivatives and doesn't not neet to implement this method. */
+ 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)
+ {
+ return false;
+ }
+ //@}
+
+ /** @name Solution Methods */
+ //@{
+ /** This method is called when the algorithm is complete so the TNLP can store/write the solution */
+ virtual void finalize_solution(SolverReturn status,
+ Index n, const Number* x, const Number* z_L, const Number* z_U,
+ Index m, const Number* g, const Number* lambda,
+ Number obj_value,
+ const IpoptData* ip_data,
+ IpoptCalculatedQuantities* ip_cq)=0;
+ /** This method is called just before finalize_solution. With
+ * this method, the algorithm returns any metadata collected
+ * during its run, including the metadata provided by the user
+ * with the above get_var_con_metadata. Each metadata can be of
+ * type string, integer, and numeric. It can be associated to
+ * either the variables or the constraints. The metadata that
+ * was associated with the primal variable vector is stored in
+ * var_..._md. The metadata associated with the constraint
+ * multipliers is stored in con_..._md. The metadata associated
+ * with the bound multipliers is stored in var_..._md, with the
+ * suffixes "_z_L", and "_z_U", denoting lower and upper
+ * bounds. */
+ virtual void finalize_metadata(Index n,
+ const StringMetaDataMapType& var_string_md,
+ const IntegerMetaDataMapType& var_integer_md,
+ const NumericMetaDataMapType& var_numeric_md,
+ Index m,
+ const StringMetaDataMapType& con_string_md,
+ const IntegerMetaDataMapType& con_integer_md,
+ const NumericMetaDataMapType& con_numeric_md)
+ {}
+
+
+ /** Intermediate Callback method for the user. Providing dummy
+ * default implementation. For details see IntermediateCallBack
+ * in IpNLP.hpp. */
+ virtual bool intermediate_callback(AlgorithmMode mode,
+ Index iter, Number obj_value,
+ Number inf_pr, Number inf_du,
+ Number mu, Number d_norm,
+ Number regularization_size,
+ Number alpha_du, Number alpha_pr,
+ Index ls_trials,
+ const IpoptData* ip_data,
+ IpoptCalculatedQuantities* ip_cq)
+ {
+ return true;
+ }
+ //@}
+
+ /** @name Methods for quasi-Newton approximation. If the second
+ * derivatives are approximated by Ipopt, it is better to do this
+ * only in the space of nonlinear variables. The following
+ * methods are call by Ipopt if the quasi-Newton approximation is
+ * selected. If -1 is returned as number of nonlinear variables,
+ * Ipopt assumes that all variables are nonlinear. Otherwise, it
+ * calls get_list_of_nonlinear_variables with an array into which
+ * the indices of the nonlinear variables should be written - the
+ * array has the lengths num_nonlin_vars, which is identical with
+ * the return value of get_number_of_nonlinear_variables(). It
+ * is assumed that the indices are counted starting with 1 in the
+ * FORTRAN_STYLE, and 0 for the C_STYLE. */
+ //@{
+ virtual Index get_number_of_nonlinear_variables()
+ {
+ return -1;
+ }
+
+ virtual bool get_list_of_nonlinear_variables(Index num_nonlin_vars,
+ Index* pos_nonlin_vars)
+ {
+ return false;
+ }
+ //@}
+
+ 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 */
+ //TNLP();
+
+ /** Copy Constructor */
+ TNLP(const TNLP&);
+
+ /** Overloaded Equals Operator */
+ void operator=(const TNLP&);
+ //@}
+ };
+
+} // namespace Ipopt
+
+#endif
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