ConicBundle::PrimalMatrix Class Reference
[Interface to ConicBundle for the Language C++ using Matrix Classes]

If in Lagrangean relaxation primal solutions are in the form of a real vector or, more generally a matrix, then an approximate primal solution can be generated by supplying primal information of this form for each epsilon subgradient within ConicBundle::MatrixFunctionOracle::evaluate(). More...

#include <MatCBSolver.hxx>

Inheritance diagram for ConicBundle::PrimalMatrix:

ConicBundle::PrimalData CH_Matrix_Classes::Matrix CH_Matrix_Classes::Memarrayuser

List of all members.

Public Member Functions

 PrimalMatrix ()
 empty matrix
 PrimalMatrix (CH_Matrix_Classes::Integer nr, CH_Matrix_Classes::Integer nc)
 generate a matrix of size nr x nc but WITHOUT initializing the memory
 PrimalMatrix (CH_Matrix_Classes::Integer r, CH_Matrix_Classes::Integer c, CH_Matrix_Classes::Real d)
 generate a matrix of size nr x nc initializing all elements to the value d
 PrimalMatrix (const PrimalMatrix &pm)
 copy constructor, *this=pm
 PrimalMatrix (const CH_Matrix_Classes::Matrix &pm)
 copy constructor, *this=pm
PrimalMatrixoperator= (const CH_Matrix_Classes::Matrix &pd)
 copy operator, *this=pm
PrimalDataclone_primal_data ()
 produces a new PrimalMatrix that is a copy of itself; the caller has to delete the returned object at some point
int assign_primal_data (const PrimalData &it)
 copy its information to *this (it must dynamic_cast to a PrimalMatrix)
int aggregate_primal_data (double myfactor, double itsfactor, const PrimalData &it)
 multiply *this Matrix with myfactor and add itsfactor*it (it must dynamic_cast to a PrimalMatrix)


Detailed Description

If in Lagrangean relaxation primal solutions are in the form of a real vector or, more generally a matrix, then an approximate primal solution can be generated by supplying primal information of this form for each epsilon subgradient within ConicBundle::MatrixFunctionOracle::evaluate().

In many applications, e.g. in Lagrangean relaxation, the convex minimization problem arises as the dual of a convex primal maximization problem. In this case one is typically interested in obtaining a primal approximate solution in addition to the dual solution. Under reasonable conditions this is possible if the primal solutions that give rise to the subgradients are aggregated along with the subgradients within the bundle algorithm. If the primal data can be represented as a CH_Matrix_Classes::Matrix then the user has to supply in the oracle for each sugradient the corresponding primal data in a PrimalMatrix and the algorithm will do the rest. Observe that a PrimalMatrix can be used exactly in the same way as a CH_Matrix_Classes::Matrix and that they are assignable among each other.

The primal data has to be supplied within ConicBundle::MatrixFunctionOracle::Evaluate() and can be retrieved via the methods ConicBundle::MatrixCBSolver::get_approximate_primal() and ConicBundle::MatrixCBSolver::get_center_primal()


Constructor & Destructor Documentation

ConicBundle::PrimalMatrix::PrimalMatrix ( CH_Matrix_Classes::Integer  nr,
CH_Matrix_Classes::Integer  nc 
) [inline]

generate a matrix of size nr x nc but WITHOUT initializing the memory

If initializing the memory externally and CONICBUNDLE_DEBUG is defined, please use set_init() via matrix.set_init(true) in order to avoid warnings concerning improper initialization


The documentation for this class was generated from the following file:

Generated on Mon Nov 8 19:36:41 2010 for ConicBundle by  doxygen 1.5.6