#include <OSBearcatSolverXij.h>
Classes | |
| class | Factory |
Public Member Functions | |
| virtual OSInstance * | getInitialRestrictedMaster () |
| OSInstance* OSBearcatSolverXij::getInitialRestrictedMaster( ){. More... | |
| OSInstance * | getSeparationInstance () |
| double | qrouteCost (const int &k, const int &l, const double *c, int *kountVar) |
| kipp – document More... | |
| void | getOptL (double **c) |
| void | getCutsTheta (const double *thetaVar, const int numThetaVar, int &numNewRows, int *&numNonz, int **&colIdx, double **&values, double *&rowLB, double *&rowUB) |
| RETURN VALUES: int numNewRows – number of new rows generated int* numNonz – number of nonzeros in each row int** colIdx – vectors column indexes of new rows double** values – vectors of matrix coefficient values of new rows double* rowLB – vector of row lower bounds double* rowUB – vector of row upper bounds. More... | |
| void | getCutsX (const double *xVar, const int numXVar, int &numNewRows, int *&numNonz, int **&colIdx, double **&values, double *&rowLB, double *&rowUB) |
| RETURN VALUES: int numNewRows – number of new rows generated int* numNonz – number of nonzeros in each row int** colIdx – vectors column indexes of new rows double** values – vectors of matrix coefficient values of new rows double* rowLB – vector of row lower bounds double* rowUB – vector of row upper bounds. More... | |
| virtual void | getBranchingCut (const double *thetaVar, const int numThetaVar, const std::map< int, int > &varConMap, int &varIdx, int &numNonz, int *&indexes, double *&values) |
| RETURN VALUES: varIdx – the variable number x_{ij} for branching numNonz – number of theta indexes in the cut indexes – the indexes of the theta variables values – the number of times the theta indexed in indexes appears in the cut note – set numNonz to zero if the generated cut variable already appears in varConMap. More... | |
| virtual void | getBranchingCut (const int *thetaIdx, const double *theta, const int numThetaVar, const std::map< int, int > &varConMap, int &varIdx, int &numNonz, int *&indexes, double *&values) |
| Sparse Version. More... | |
| void | getCutsMultiCommod (const double *thetaVar, const int numThetaVar, int &numNewRows, int *&numNonz, int **&colIdx, double **&values, double *&rowLB, double *&rowUB) |
| This is the routine that generates the multi-item cuts. More... | |
| int | getBranchingVar (const double *theta, const int numThetaVar) |
| RETURN VALUES: return the integer index of a fractional x_{ij} variable. More... | |
| int | getBranchingVar (const int *thetaIdx, const double *theta, const int numThetaVar) |
| Sparse Version. More... | |
| virtual void | getColumns (const double *yA, const int numARows, const double *yB, const int numBRows, int &numNewColumns, int *&numNonz, double *&cost, int **&rowIdx, double **&values, double &lowerBound) |
| RETURN VALUES: int numNewColumns – number of new columns generated int* numNonz – number of nonzeros in each column double* cost – the objective function coefficient on each new column double** rowIdx – vectors row indexes of new columns double** values – vectors of matrix coefficient values of new columns double lowerBound – the lowerBound, this is a value on the LP relaxation. More... | |
| void | getOptions (OSOption *osoption) |
| void | getVariableIndexMap () |
| this method will populate: std::map<std::pair<int, int>,int>m_xVarIndexMap this gives us More... | |
| void | permuteHubs () |
| this method will calculate a permuation of the hubs so that they are in ascending order, this will make the dynamic program in the v variables faster More... | |
| void | calcReducedCost (const double *yA, const double *yB) |
| calculate the reduced costs c – input of the objective function costs yA – dual values on node assignment – coupling constraints yB – dual values on tour breaking constraints d – reduced with convexity dual value More... | |
| void | createVariableNames () |
| void | createAmatrix () |
| virtual void | initializeDataStructures () |
| allocate memory and initialize arrays More... | |
| void | getInitialSolution () |
| generate an intitial feasible solution in theta space for the initial master More... | |
| virtual void | resetMaster (std::map< int, int > &inVars, OsiSolverInterface *si) |
| INPUT: More... | |
| double | getRouteDistance (int numNodes, int hubIndex, CoinSolver *solver, std::vector< int > zk, double *xVar) |
| call this method to get a minimum TSP tour for a given assignment of nodes to routes INPUT: int numNodes – number of cities/nodes in tour int hubIndex – indexes the hub index CoinSolver* solver – the coin solver numNodes*numNodes - numNodes entries, we are assuming zk – indexes the non-hub nodes assigned this route asymmetric More... | |
| CoinSolver * | getTSP (int numNodes, double *cost) |
| call this method to get a TSP instance More... | |
| CoinSolver * | getMultiCommodInstance (int hubIndex) |
| call this method to get an instance that is used to generate a multicommodity cut More... | |
| void | getFeasibleSolution () |
| call this method to get generate an instance of the generalized assignment problem and find a feasible solution to the problem More... | |
| bool | OneOPT () |
| try and find a feasible solution, return false if solution not feasible More... | |
| virtual void | pauHana (std::vector< int > &m_zOptIndexes, std::vector< double > &m_zRootLPx_vals, int numNodes, int numColsGen, std::string message) |
| double | calcNonlinearRelax (std::vector< double > &m_zRootLPx_vals) |
| calculate the nonlinear relaxation value for an LP solution More... | |
| OSBearcatSolverXij () | |
| Default Constructor. More... | |
| OSBearcatSolverXij (OSOption *osoption) | |
| Second Constructor. More... | |
| ~OSBearcatSolverXij () | |
| Default Destructor. More... | |
 Public Member Functions inherited from OSDecompSolver | |
| OSDecompSolver () | |
| Default Constructor. More... | |
| OSDecompSolver (OSOption *osoption) | |
| Constructor with OSOption Arg. More... | |
| virtual | ~OSDecompSolver ()=0 |
| Default destructor. More... | |
Public Attributes | |
| std::map< int, std::string > | m_tmpVarMap |
| std::map< std::pair< int, int > , int > | m_xVarIndexMap |
| m_xVarIndexMap takes a variable indexed by (i,j) and returns the index of the variable in one dimension More... | |
| int * | m_hubPoint |
| m_hubPoint[ k] points to the the k'th hub that we use in getOptL More... | |
| std::string | m_initOSiLFile |
| std::map< int, std::map< int, std::vector< int > > > | m_initSolMap |
| the index on the outer map is on the solution number, the index on the inner map indexes the route number, the vector is the list of nodes assigned to that route More... | |
| std::vector< CoinSolver * > | m_multCommodCutSolvers |
| m_multCommodCutSolvers is a vector of solvers, one solver for each hub, used to find multicommodity flow cuts for the given hub More... | |
| bool | m_use1OPTstart |
| if m_use1OPTstart is true we use the option file to fix the nodes to hubs found by SK's 1OPT heuristic More... | |
| int | m_maxThetaNonz |
| m_maxMasterNonz is the maximumn number of nonzero elements we allow in the transformation matrix betwee the theta variables and the xij variables More... | |
| int * | m_routeCapacity |
| the route capacity – bus seating limit this can vary with the route/hub More... | |
| int * | m_routeMinPickup |
| the minimum number of students that we pickup on a route this can vary with the route/hub More... | |
| int * | m_upperBoundL |
| largest possible L-value on a route – this will be the minimum of m_routeCapacity and total demand More... | |
| int * | m_lowerBoundL |
| smallest possible L-value on a route for now this will equal More... | |
| int | m_upperBoundLMax |
| largest possible L-value over all routes More... | |
| int | m_minDemand |
| m_minDemand is the value of the minimum demand node – it is not the minimum demand that must be carried on a route More... | |
| int * | m_demand |
| m_demand is the vector of node demands More... | |
| std::string * | m_nodeName |
| m_nodeName is the vector of node names More... | |
| double * | m_cost |
| the distance/cost vectors More... | |
| bool | m_costSetInOption |
| m_costSetInOption is true if the costs are set using the OSOption file More... | |
| double ** | m_rc |
| the reduced cost vector for each k, we asssume order is (l, i, j) More... | |
| double * | m_optValHub |
| double ** | m_u |
| double ** | m_v |
| int ** | m_px |
| int ** | m_tx |
| double ** | m_g |
| int * | m_varIdx |
| int * | m_optL |
| int * | m_optD |
| double ** | m_vv |
| int ** | m_vvpnt |
| int | m_totalDemand |
| int | m_numberOfSolutions |
| int * | m_tmpScatterArray |
| double | m_lowerBnd |
| int * | m_newColumnNonz |
| double * | m_costVec |
| int ** | m_newColumnRowIdx |
| double ** | m_newColumnRowValue |
| int * | m_newRowNonz |
| int ** | m_newRowColumnIdx |
| double ** | m_newRowColumnValue |
| double * | m_newRowUB |
| double * | m_newRowLB |
| int * | branchCutIndexes |
| double * | branchCutValues |
| double * | m_thetaCost |
| int * | m_convexityRowIndex |
| m_convexityRowIndex holds the index of the convexity row that the theta columns are in. More... | |
| int * | m_BmatrixRowIndex |
| m_BmatrixRowIndex holds the index of the convexity row that the constraint corresponds to, this is for the multicommodity constraints – if the constraint applies to theta regardless of k, then the value is -1 More... | |
| int * | m_separationIndexMap |
| m_separationIndexMap maps the variable index into the appropriate row in the separation problem for the tour breaking constraints More... | |
| OSInstance * | m_osinstanceSeparation |
| ClpSimplex * | m_separationClpModel |
| Public Attributes inherited from OSDecompSolver | |
| OSInstance * | m_osinstanceMaster |
| int | m_multiCommodCutLimit |
| int | m_numMultCuts |
| OSDecompParam | m_osDecompParam |
| share the parameters with the decomposition solver More... | |
| double | m_bestIPValue |
| double | m_bestLPValue |
| double | m_rootLPValue |
| int * | m_thetaPnt |
| int * | m_thetaIndex |
| int | m_numThetaVar |
| int | m_numThetaNonz |
| int * | m_pntBmatrix |
| int * | m_BmatrixIdx |
| double * | m_BmatrixVal |
| std::set< std::pair< int, double > > | intVarSet |
| intVarSet holds and std::pair where the first element is the index of an integer variable and the second is the variable upper bound More... | |
| int | m_numHubs |
| m_numHubs is the number of hubs/routes More... | |
| int | m_numNodes |
| m_numNodes is the number of nodes (both pickup and hub) in the model More... | |
| int * | m_pntAmatrix |
| int * | m_Amatrix |
| int | m_numBmatrixCon |
| m_numBmatrixCon is the number of constraints in B - 1, we have the -1 because: m_pntBmatrix[ k] points to the start of constraint k and m_pntBmatrix[ m_numBmatrixCon ] is equal to m_numBmatrixNonz More... | |
| int | m_numBmatrixNonz |
| int | m_maxBmatrixNonz |
| m_maxBmatrixNonz is the maximum number of nonzero elements in the B matrix constraints More... | |
| int | m_maxBmatrixCon |
| m_maxBmatrixCon is the maximum number of B matrix constraints it is the number of tour breaking constraints plus variable branch constraints More... | |
| int | m_maxMasterColumns |
| m_maxMasterColumns is the maximumn number of columns we allow in the master More... | |
| int | m_maxMasterRows |
| m_maxMasterColumns is the maximumn number of rows we allow in the master, in this application it is equal to m_maxBmatrixCon plus m_numNodes – we therefore do not need to read this from an option file as we might for other problems More... | |
| std::string * | m_variableNames |
| OSOption * | m_osoption |
Detailed Description
Definition at line 31 of file OSBearcatSolverXij.h.
Constructor & Destructor Documentation
| OSBearcatSolverXij::OSBearcatSolverXij | ( | ) |
Default Constructor.
Definition at line 68 of file OSBearcatSolverXij.cpp.
| OSBearcatSolverXij::OSBearcatSolverXij | ( | OSOption * | osoption | ) |
Second Constructor.
Definition at line 72 of file OSBearcatSolverXij.cpp.
| OSBearcatSolverXij::~OSBearcatSolverXij | ( | ) |
Default Destructor.
Definition at line 360 of file OSBearcatSolverXij.cpp.
Member Function Documentation
|
virtual |
OSInstance* OSBearcatSolverXij::getInitialRestrictedMaster( ){.
std::cout << "Executing OSBearcatSolverXij::getInitialRestrictedMaster( )" << std::endl;
define the classes FileUtil *fileUtil = NULL; OSiLReader *osilreader = NULL; DefaultSolver *solver = NULL; OSInstance *osinstance = NULL;
end classes
std::string testFileName;
std::string osil;
std::vector< int> indexes; fileUtil = new FileUtil();
std::map<int, std::map<int, std::vector<int> > >::iterator mit;
std::map<int, std::vector<int> >::iterator mit2;
std::vector<int>::iterator vit;
m_osinstanceMaster = NULL;
add linear constraint coefficients number of values will nodes.size() the coefficients in the node constraints plus coefficients in convexity constraints which is the number of varaibles int kountNonz; int kount; int numThetaVar = m_numberOfSolutions*m_numHubs; double values = new double[ m_numberOfSolutions(m_numNodes-m_numHubs) + numThetaVar]; int indexes = new int[ m_numberOfSolutions(m_numNodes-m_numHubs) + numThetaVar]; int *starts = new int[ numThetaVar + 1]; kount = 0;
starts[ 0] = 0;
int startsIdx; startsIdx = 0;
std::vector<IndexValuePair*> primalValPair;
try {
if(m_initOSiLFile.size() == 0) throw ErrorClass("OSiL file to generate restricted master missing");
osil = fileUtil->getFileAsString( m_initOSiLFile.c_str());
osilreader = new OSiLReader();
osinstance = osilreader->readOSiL(osil);
int i;
int j;
int k;
fill in the cost vector first the x vector starts at 2*m_numHubs
int idx1;
int idx2;
idx2 = 0; //zRouteDemand have 0 coefficients in obj
fill in m_cost from the cost coefficient in osil for(k = 0; k < m_numHubs; k++){
idx1 = 0;
for(i = 0; i < m_numNodes; i++){
for(j = 0; j < i; j++){
m_cost[k][idx1++ ] = osinstance->instanceData->objectives->obj[0]->coef[ idx2++ ]->value;
}
for(j = i + 1; j < m_numNodes; j++){
m_cost[k][idx1++ ] = osinstance->instanceData->objectives->obj[0]->coef[ idx2++ ]->value;
}
}
}
get variable names for checking purposes std::string* varNames; varNames = osinstance->getVariableNames();
start building the restricted master here
m_osinstanceMaster = new OSInstance();
m_osinstanceMaster->setInstanceDescription("The Initial Restricted Master");
first the variables m_osinstanceMaster->setVariableNumber( m_numberOfSolutions*m_numHubs);
now add the objective function m_osinstanceMaster->setObjectiveNumber( 1); SparseVector *objcoeff = new SparseVector( m_numberOfSolutions*m_numHubs);
now the constraints m_osinstanceMaster->setConstraintNumber( m_numNodes);
addVariable(int index, string name, double lowerBound, double upperBound, char type, double init, string initString); we could use setVariables() and add all the variable with one method call – below is easier
int varNumber;
varNumber = 0;
std::string masterVarName;
kountNonz = 0;
now get the primal solution solve the model for solution in the osoption object for ( mit = m_initSolMap.begin() ; mit != m_initSolMap.end(); mit++ ){
kipp change upper and lower bounds here on z variables loop over nodes and routes and set bound set kount to the start of the z variables go past the x variables kount = 2*m_numHubs + m_numHubs*(m_numNodes*m_numNodes - m_numNodes); osinstance->bVariablesModified = true; for ( mit2 = mit->second.begin() ; mit2 != mit->second.end(); mit2++ ){ //we are looping over routes in solution mit
startsIdx++;
starts[ startsIdx ] = kountNonz + mit2->second.size() + 1; //the +1 comes from the convexity row
make sure all lower bounds on z variables on this route back to 0.0 for(i = 0; i < m_numNodes; i++){ osinstance->instanceData->variables->var[ kount + mit2->first*m_numNodes + i]->lb = 0.0; }
for ( vit = mit2->second.begin() ; vit != mit2->second.end(); vit++ ){
osinstance->instanceData->variables->var[ kount + mit2->first*m_numNodes + *vit]->lb = 1.0;
std::cout << "FIXING LOWER BOUND ON VARIABLE " << osinstance->getVariableNames()[ kount + mit2->first*m_numNodes + *vit ] << std::endl;
values[ kountNonz] = 1.0;
indexes[ kountNonz ] = *vit - m_numHubs ; //0 based counting
kountNonz++;
}
now for the convexity row coefficient values[ kountNonz] = 1; indexes[ kountNonz ] = m_numNodes - m_numHubs + mit2->first ; kountNonz++;
}
solver = new CoinSolver();
solver->sSolverName ="cbc";
solver->osinstance = osinstance;
solver->buildSolverInstance();
solver->solve();
get the solver solution status
std::cout << "Solution Status = " << solver->osresult->getSolutionStatusType( 0 ) << std::endl;
get the optimal objective function value
primalValPair = solver->osresult->getOptimalPrimalVariableValues( 0);
loop over routes again to create master objective coefficients
for(k = 0; k < m_numHubs; k++){
lets get the x variables the variables for this route should be from 2*numHubs + k*(numNodes - 1*)*(numNodes - 1) idx1 = 2*m_numHubs + k*m_numNodes*(m_numNodes - 1); idx2 = idx1 + m_numNodes*(m_numNodes - 1); end of x variables
std::cout << "HUB " << k << " VARIABLES" << std::endl;
for(i = idx1; i < idx2; i++){
if( primalValPair[ i]->value > .1 ){
std::cout << osinstance->getVariableNames()[ primalValPair[ i]->idx ] << std::endl; std::cout << m_variableNames[ primalValPair[ i]->idx - k*(m_numNodes - 1)*m_numNodes - 2*m_numHubs ] << std::endl; m_thetaIndex[ m_numThetaNonz++ ] = primalValPair[ i]->idx - k*(m_numNodes - 1)*m_numNodes - 2*m_numHubs; }
} m_convexityRowIndex[ m_numThetaVar] = k; m_thetaCost[ m_numThetaVar++ ] = primalValPair[ k]->value*primalValPair[ k + m_numHubs]->value; m_thetaPnt[ m_numThetaVar ] = m_numThetaNonz;
masterVarName = makeStringFromInt("theta(", k); masterVarName += makeStringFromInt(",", mit->first); masterVarName += ")"; intVarSet.insert ( std::pair<int,double>(varNumber, 1.0) ); m_osinstanceMaster->addVariable(varNumber++, masterVarName, 0, 1, 'C');
std::cout << "Optimal Objective Value = " << primalValPair[ k]->value*primalValPair[ k + m_numHubs]->value << std::endl;
objcoeff->indexes[ k + (mit->first)*m_numHubs] = k + (mit->first)*m_numHubs; objcoeff->values[ k + (mit->first)*m_numHubs] = primalValPair[ k]->value*primalValPair[ k + m_numHubs]->value;
std::cout << osinstance->getVariableNames()[ k ] << std::endl;
std::cout << osinstance->getVariableNames()[ k + m_numHubs ] << std::endl;
}//end for on k -- hubs
primalValPair.clear();
delete solver;
solver = NULL;
}//end for on number of solutions
add the constraints add the row saying we must visit each node for( i = 0; i < m_numNodes - m_numHubs ; i++){
m_osinstanceMaster->addConstraint(i, makeStringFromInt("visitNode_", i + m_numHubs) , 1.0, 1.0, 0);
}
kount = 0;
add the convexity row for( i = m_numNodes - m_numHubs; i < m_numNodes ; i++){
m_osinstanceMaster->addConstraint(i, makeStringFromInt("convexityRowRoute_", kount++ ) , 1.0, 1.0, 0);
}
m_osinstanceMaster->addObjective(-1, "objfunction", "min", 0.0, 1.0, objcoeff);
std::cout << "kountNonz = " << kountNonz << std::endl;
add the linear constraints coefficients m_osinstanceMaster->setLinearConstraintCoefficients(kountNonz , true, values, 0, kountNonz - 1, indexes, 0, kountNonz - 1, starts, 0, startsIdx);
std::cout << m_osinstanceMaster->printModel() << std::endl;
delete objcoeff;
delete[] values; delete[] starts; delete[] indexes; delete osilreader; osilreader = NULL;
} catch (const ErrorClass& eclass) {
std::cout << std::endl << std::endl << std::endl;
if (osilreader != NULL)
delete osilreader;
if (solver != NULL)
delete solver;
Problem with the parser throw ErrorClass(eclass.errormsg); }
delete fileUtil; fileUtil = NULL;
return m_osinstanceMaster; }//end generateInitialRestrictedMaster
Implements OSDecompSolver.
Definition at line 1632 of file OSBearcatSolverXij.cpp.
| OSInstance * OSBearcatSolverXij::getSeparationInstance | ( | ) |
Definition at line 3776 of file OSBearcatSolverXij.cpp.
| double OSBearcatSolverXij::qrouteCost | ( | const int & | k, |
| const int & | l, | ||
| const double * | c, | ||
| int * | kountVar | ||
| ) |
kipp – document
Definition at line 727 of file OSBearcatSolverXij.cpp.
| void OSBearcatSolverXij::getOptL | ( | double ** | c | ) |
Definition at line 570 of file OSBearcatSolverXij.cpp.
|
virtual |
RETURN VALUES: int numNewRows – number of new rows generated int* numNonz – number of nonzeros in each row int** colIdx – vectors column indexes of new rows double** values – vectors of matrix coefficient values of new rows double* rowLB – vector of row lower bounds double* rowUB – vector of row upper bounds.
INPUT: double* thetaVar – the vector of primal master values int numThetaVar – size of master primal vector
Implements OSDecompSolver.
Definition at line 2176 of file OSBearcatSolverXij.cpp.
| void OSBearcatSolverXij::getCutsX | ( | const double * | xVar, |
| const int | numXVar, | ||
| int & | numNewRows, | ||
| int *& | numNonz, | ||
| int **& | colIdx, | ||
| double **& | values, | ||
| double *& | rowLB, | ||
| double *& | rowUB | ||
| ) |
RETURN VALUES: int numNewRows – number of new rows generated int* numNonz – number of nonzeros in each row int** colIdx – vectors column indexes of new rows double** values – vectors of matrix coefficient values of new rows double* rowLB – vector of row lower bounds double* rowUB – vector of row upper bounds.
INPUT: double* xVar – the vector of primal values int numXVar – size of master primal vector
Definition at line 3124 of file OSBearcatSolverXij.cpp.
|
virtual |
RETURN VALUES: varIdx – the variable number x_{ij} for branching numNonz – number of theta indexes in the cut indexes – the indexes of the theta variables values – the number of times the theta indexed in indexes appears in the cut note – set numNonz to zero if the generated cut variable already appears in varConMap.
INPUT: double* thetaVar – the vector of primal master values int numThetaVar – size of master primal vector varConMap – the map of variables in x_{ij} space to a consraint number
Implements OSDecompSolver.
Definition at line 4306 of file OSBearcatSolverXij.cpp.
|
virtual |
Sparse Version.
RETURN VALUES: varIdx – the variable number x_{ij} for branching numNonz – number of theta indexes in the cut indexes – the indexes of the theta variables values – the number of times the theta indexed in indexes appears in the cut note – set numNonz to zero if the generated cut variable already appears in varConMap
INPUT: double* theta – the vector of primal master values int numThetaVar – size of master primal vector varConMap – the map of variables in x_{ij} space to a consraint number
Implements OSDecompSolver.
Definition at line 4388 of file OSBearcatSolverXij.cpp.
|
virtual |
This is the routine that generates the multi-item cuts.
RETURN VALUES: int numNewRows – number of new rows generated int* numNonz – number of nonzeros in each row int** colIdx – vectors column indexes of new rows double** values – vectors of matrix coefficient values of new rows double* rowLB – vector of row lower bounds double* rowUB – vector of row upper bounds
INPUT: double* thetaVar – the vector of primal master values int numThetaVar – size of master primal vector
kount = 0;
for(i = 0; i < m_numNodes; i++){
for(j = 0; j < i; j++){ //j < i
indexPair.first = i;
indexPair.second = j;
xVarIndexMap[ indexPair] = kount;
kount++;
}
for(j = i+1; j < m_numNodes; j++){ // i < j
indexPair.first = i;
indexPair.second = j;
xVarIndexMap[ indexPair] = kount;
kount++;
}
}
end construct map
Implements OSDecompSolver.
Definition at line 2558 of file OSBearcatSolverXij.cpp.
RETURN VALUES: return the integer index of a fractional x_{ij} variable.
INPUT: double* theta – the vector of primal master values int numThetaVar – size of master primal vector
Definition at line 4020 of file OSBearcatSolverXij.cpp.
| int OSBearcatSolverXij::getBranchingVar | ( | const int * | thetaIdx, |
| const double * | theta, | ||
| const int | numThetaVar | ||
| ) |
Sparse Version.
RETURN VALUES: return the integer index of a fractional x_{ij} variable
INPUT: int* thetaIdx – index vector of nonzero theta variables double* theta – the sparse vector of primal master values int numThetaVar – size of master primal vector
Definition at line 4161 of file OSBearcatSolverXij.cpp.
|
virtual |
RETURN VALUES: int numNewColumns – number of new columns generated int* numNonz – number of nonzeros in each column double* cost – the objective function coefficient on each new column double** rowIdx – vectors row indexes of new columns double** values – vectors of matrix coefficient values of new columns double lowerBound – the lowerBound, this is a value on the LP relaxation.
INPUT: double* y – the vector of dual values int numRows – size of dual vector
int ivalue;
int jvalue;
for(j = 0; j < kountVar; j++){
startPntInc = k*m_upperBoundL*(m_numNodes*m_numNodes - m_numNodes) + (m_optL[ k] - 1)*(m_numNodes*m_numNodes - m_numNodes);
std::cout << "Variable Index = " << m_varIdx[ j] - startPntInc ;
std::cout << " Variable = " << m_variableNames[ m_varIdx[ j] - startPntInc ] << std::endl ;
tmp – get the node
tmp = fmod(m_varIdx[ j] - startPntInc, m_numNodes) ;
ivalue = floor( (m_varIdx[ j] - startPntInc)/(m_numNodes - 1) );
jvalue = (m_varIdx[ j] - startPntInc) - ivalue*(m_numNodes - 1);
std::cout << " i NODE NUMBER = " << ivalue ;
if( jvalue > ivalue ){
std::cout << " j NODE NUMBER = " << jvalue + 1 << std::endl;
}else{
std::cout << " j NODE NUMBER = " << jvalue << std::endl;
}
}
std::cout << "Route True Cost = " << m_costVec[ k] << std::endl;
Implements OSDecompSolver.
Definition at line 1074 of file OSBearcatSolverXij.cpp.
Definition at line 1849 of file OSBearcatSolverXij.cpp.
| void OSBearcatSolverXij::getVariableIndexMap | ( | ) |
this method will populate: std::map<std::pair<int, int>,int>m_xVarIndexMap this gives us
Definition at line 6105 of file OSBearcatSolverXij.cpp.
| void OSBearcatSolverXij::permuteHubs | ( | ) |
this method will calculate a permuation of the hubs so that they are in ascending order, this will make the dynamic program in the v variables faster
Definition at line 6136 of file OSBearcatSolverXij.cpp.
| void OSBearcatSolverXij::calcReducedCost | ( | const double * | yA, |
| const double * | yB | ||
| ) |
calculate the reduced costs c – input of the objective function costs yA – dual values on node assignment – coupling constraints yB – dual values on tour breaking constraints d – reduced with convexity dual value
Definition at line 3342 of file OSBearcatSolverXij.cpp.
| void OSBearcatSolverXij::createVariableNames | ( | ) |
Definition at line 3439 of file OSBearcatSolverXij.cpp.
| void OSBearcatSolverXij::createAmatrix | ( | ) |
Definition at line 3480 of file OSBearcatSolverXij.cpp.
|
virtual |
allocate memory and initialize arrays
m_u[i, l] – this will be the minimum cost of reaching node i on a q-route with demand l, note that m_u[ i] has dimension m_upperBoundL + 1 so the possible values for l are l = 0, 1, , m_upperBoundL – l is the actual value of demand
Implements OSDecompSolver.
Definition at line 112 of file OSBearcatSolverXij.cpp.
| void OSBearcatSolverXij::getInitialSolution | ( | ) |
generate an intitial feasible solution in theta space for the initial master
Definition at line 4474 of file OSBearcatSolverXij.cpp.
|
virtual |
INPUT:
- Parameters
-
dstd::map<int,int> &inVars – the mapping of variables, the first index is the variable number before resetting, the second index is the variable number after the reset OsiSolverInterface *si – the solver interface that corresponds to the master this is what gets rebuilt
Implements OSDecompSolver.
Definition at line 4531 of file OSBearcatSolverXij.cpp.
| double OSBearcatSolverXij::getRouteDistance | ( | int | numNodes, |
| int | hubIndex, | ||
| CoinSolver * | solver, | ||
| std::vector< int > | zk, | ||
| double * | xVar | ||
| ) |
call this method to get a minimum TSP tour for a given assignment of nodes to routes INPUT: int numNodes – number of cities/nodes in tour int hubIndex – indexes the hub index CoinSolver* solver – the coin solver numNodes*numNodes - numNodes entries, we are assuming zk – indexes the non-hub nodes assigned this route asymmetric
OUTPUT: xVar the optimal solution
Definition at line 4910 of file OSBearcatSolverXij.cpp.
| CoinSolver * OSBearcatSolverXij::getTSP | ( | int | numNodes, |
| double * | cost | ||
| ) |
call this method to get a TSP instance
INPUT: int numNodes – number of cities/nodes in tour double* cost – the cost vector, this should have
RETURN: pointer to a CoinSolver with a TSP instance
Definition at line 5109 of file OSBearcatSolverXij.cpp.
| CoinSolver * OSBearcatSolverXij::getMultiCommodInstance | ( | int | hubIndex | ) |
call this method to get an instance that is used to generate a multicommodity cut
INPUT: hubIndex is the index associated with the hub for which we are looking for a cut RETURN: pointer to a CoinSolver with a cut generator instance
Definition at line 5611 of file OSBearcatSolverXij.cpp.
| void OSBearcatSolverXij::getFeasibleSolution | ( | ) |
call this method to get generate an instance of the generalized assignment problem and find a feasible solution to the problem
INPUT:
RETURN: void
Definition at line 5892 of file OSBearcatSolverXij.cpp.
| bool OSBearcatSolverXij::OneOPT | ( | ) |
try and find a feasible solution, return false if solution not feasible
Definition at line 5316 of file OSBearcatSolverXij.cpp.
|
virtual |
Implements OSDecompSolver.
Definition at line 3529 of file OSBearcatSolverXij.cpp.
| double OSBearcatSolverXij::calcNonlinearRelax | ( | std::vector< double > & | m_zRootLPx_vals | ) |
calculate the nonlinear relaxation value for an LP solution
Definition at line 3630 of file OSBearcatSolverXij.cpp.
Member Data Documentation
| std::map<int, std::string> OSBearcatSolverXij::m_tmpVarMap |
Definition at line 39 of file OSBearcatSolverXij.h.
m_xVarIndexMap takes a variable indexed by (i,j) and returns the index of the variable in one dimension
Definition at line 44 of file OSBearcatSolverXij.h.
| int* OSBearcatSolverXij::m_hubPoint |
m_hubPoint[ k] points to the the k'th hub that we use in getOptL
Definition at line 50 of file OSBearcatSolverXij.h.
| std::string OSBearcatSolverXij::m_initOSiLFile |
Definition at line 53 of file OSBearcatSolverXij.h.
the index on the outer map is on the solution number, the index on the inner map indexes the route number, the vector is the list of nodes assigned to that route
Definition at line 59 of file OSBearcatSolverXij.h.
| std::vector<CoinSolver*> OSBearcatSolverXij::m_multCommodCutSolvers |
m_multCommodCutSolvers is a vector of solvers, one solver for each hub, used to find multicommodity flow cuts for the given hub
Definition at line 65 of file OSBearcatSolverXij.h.
| bool OSBearcatSolverXij::m_use1OPTstart |
if m_use1OPTstart is true we use the option file to fix the nodes to hubs found by SK's 1OPT heuristic
Definition at line 70 of file OSBearcatSolverXij.h.
| int OSBearcatSolverXij::m_maxThetaNonz |
m_maxMasterNonz is the maximumn number of nonzero elements we allow in the transformation matrix betwee the theta variables and the xij variables
Definition at line 76 of file OSBearcatSolverXij.h.
| int* OSBearcatSolverXij::m_routeCapacity |
the route capacity – bus seating limit this can vary with the route/hub
Definition at line 84 of file OSBearcatSolverXij.h.
| int* OSBearcatSolverXij::m_routeMinPickup |
the minimum number of students that we pickup on a route this can vary with the route/hub
Definition at line 90 of file OSBearcatSolverXij.h.
| int* OSBearcatSolverXij::m_upperBoundL |
largest possible L-value on a route – this will be the minimum of m_routeCapacity and total demand
Definition at line 98 of file OSBearcatSolverXij.h.
| int* OSBearcatSolverXij::m_lowerBoundL |
smallest possible L-value on a route for now this will equal
Definition at line 104 of file OSBearcatSolverXij.h.
| int OSBearcatSolverXij::m_upperBoundLMax |
largest possible L-value over all routes
Definition at line 107 of file OSBearcatSolverXij.h.
| int OSBearcatSolverXij::m_minDemand |
m_minDemand is the value of the minimum demand node – it is not the minimum demand that must be carried on a route
Definition at line 113 of file OSBearcatSolverXij.h.
| int* OSBearcatSolverXij::m_demand |
m_demand is the vector of node demands
Definition at line 116 of file OSBearcatSolverXij.h.
| std::string* OSBearcatSolverXij::m_nodeName |
m_nodeName is the vector of node names
Definition at line 119 of file OSBearcatSolverXij.h.
| double* OSBearcatSolverXij::m_cost |
the distance/cost vectors
Definition at line 122 of file OSBearcatSolverXij.h.
| bool OSBearcatSolverXij::m_costSetInOption |
m_costSetInOption is true if the costs are set using the OSOption file
Definition at line 127 of file OSBearcatSolverXij.h.
| double** OSBearcatSolverXij::m_rc |
the reduced cost vector for each k, we asssume order is (l, i, j)
Definition at line 132 of file OSBearcatSolverXij.h.
| double* OSBearcatSolverXij::m_optValHub |
Definition at line 136 of file OSBearcatSolverXij.h.
| double** OSBearcatSolverXij::m_u |
Definition at line 140 of file OSBearcatSolverXij.h.
| double** OSBearcatSolverXij::m_v |
Definition at line 141 of file OSBearcatSolverXij.h.
| int** OSBearcatSolverXij::m_px |
Definition at line 142 of file OSBearcatSolverXij.h.
| int** OSBearcatSolverXij::m_tx |
Definition at line 143 of file OSBearcatSolverXij.h.
| double** OSBearcatSolverXij::m_g |
Definition at line 144 of file OSBearcatSolverXij.h.
| int* OSBearcatSolverXij::m_varIdx |
Definition at line 145 of file OSBearcatSolverXij.h.
| int* OSBearcatSolverXij::m_optL |
Definition at line 150 of file OSBearcatSolverXij.h.
| int* OSBearcatSolverXij::m_optD |
Definition at line 151 of file OSBearcatSolverXij.h.
| double** OSBearcatSolverXij::m_vv |
Definition at line 152 of file OSBearcatSolverXij.h.
| int** OSBearcatSolverXij::m_vvpnt |
Definition at line 153 of file OSBearcatSolverXij.h.
| int OSBearcatSolverXij::m_totalDemand |
Definition at line 157 of file OSBearcatSolverXij.h.
| int OSBearcatSolverXij::m_numberOfSolutions |
Definition at line 158 of file OSBearcatSolverXij.h.
| int* OSBearcatSolverXij::m_tmpScatterArray |
Definition at line 163 of file OSBearcatSolverXij.h.
| double OSBearcatSolverXij::m_lowerBnd |
Definition at line 166 of file OSBearcatSolverXij.h.
| int* OSBearcatSolverXij::m_newColumnNonz |
Definition at line 167 of file OSBearcatSolverXij.h.
| double* OSBearcatSolverXij::m_costVec |
Definition at line 168 of file OSBearcatSolverXij.h.
| int** OSBearcatSolverXij::m_newColumnRowIdx |
Definition at line 169 of file OSBearcatSolverXij.h.
| double** OSBearcatSolverXij::m_newColumnRowValue |
Definition at line 170 of file OSBearcatSolverXij.h.
| int* OSBearcatSolverXij::m_newRowNonz |
Definition at line 173 of file OSBearcatSolverXij.h.
| int** OSBearcatSolverXij::m_newRowColumnIdx |
Definition at line 174 of file OSBearcatSolverXij.h.
| double** OSBearcatSolverXij::m_newRowColumnValue |
Definition at line 175 of file OSBearcatSolverXij.h.
| double* OSBearcatSolverXij::m_newRowUB |
Definition at line 176 of file OSBearcatSolverXij.h.
| double* OSBearcatSolverXij::m_newRowLB |
Definition at line 177 of file OSBearcatSolverXij.h.
| int* OSBearcatSolverXij::branchCutIndexes |
Definition at line 180 of file OSBearcatSolverXij.h.
| double* OSBearcatSolverXij::branchCutValues |
Definition at line 181 of file OSBearcatSolverXij.h.
| double* OSBearcatSolverXij::m_thetaCost |
Definition at line 190 of file OSBearcatSolverXij.h.
| int* OSBearcatSolverXij::m_convexityRowIndex |
m_convexityRowIndex holds the index of the convexity row that the theta columns are in.
If the theta is an artificial variable this value is -1
Definition at line 196 of file OSBearcatSolverXij.h.
| int* OSBearcatSolverXij::m_BmatrixRowIndex |
m_BmatrixRowIndex holds the index of the convexity row that the constraint corresponds to, this is for the multicommodity constraints – if the constraint applies to theta regardless of k, then the value is -1
Definition at line 204 of file OSBearcatSolverXij.h.
| int* OSBearcatSolverXij::m_separationIndexMap |
m_separationIndexMap maps the variable index into the appropriate row in the separation problem for the tour breaking constraints
Definition at line 211 of file OSBearcatSolverXij.h.
| OSInstance* OSBearcatSolverXij::m_osinstanceSeparation |
Definition at line 214 of file OSBearcatSolverXij.h.
| ClpSimplex* OSBearcatSolverXij::m_separationClpModel |
Definition at line 217 of file OSBearcatSolverXij.h.
The documentation for this class was generated from the following files:
- /tmp/OS-2.10.2/OS/applications/columnGen/code/OSBearcatSolverXij.h
- /tmp/OS-2.10.2/OS/applications/columnGen/code/OSBearcatSolverXij.cpp
