limp-cbc-0.3.2.0: cbits/coin/CbcHeuristicVND.cpp
// $Id: CbcHeuristicVND.cpp 1902 2013-04-10 16:58:16Z stefan $
// Copyright (C) 2006, International Business Machines
// Corporation and others. All Rights Reserved.
// This code is licensed under the terms of the Eclipse Public License (EPL).
// edwin 12/5/09 carved out of CbcHeuristicRINS
#if defined(_MSC_VER)
// Turn off compiler warning about long names
# pragma warning(disable:4786)
#endif
#include <cassert>
#include <cstdlib>
#include <cmath>
#include <cfloat>
#include "OsiSolverInterface.hpp"
#include "CbcModel.hpp"
#include "CbcMessage.hpp"
#include "CbcHeuristicVND.hpp"
#include "CbcBranchActual.hpp"
#include "CbcStrategy.hpp"
#include "CglPreProcess.hpp"
// Default Constructor
CbcHeuristicVND::CbcHeuristicVND()
: CbcHeuristic()
{
numberSolutions_ = 0;
numberSuccesses_ = 0;
numberTries_ = 0;
lastNode_ = -999999;
howOften_ = 100;
decayFactor_ = 0.5;
baseSolution_ = NULL;
whereFrom_ = 1 + 8 + 255 * 256;
stepSize_ = 0;
k_ = 0;
kmax_ = 0;
nDifferent_ = 0;
}
// Constructor with model - assumed before cuts
CbcHeuristicVND::CbcHeuristicVND(CbcModel & model)
: CbcHeuristic(model)
{
numberSolutions_ = 0;
numberSuccesses_ = 0;
numberTries_ = 0;
lastNode_ = -999999;
howOften_ = 100;
decayFactor_ = 0.5;
assert(model.solver());
int numberColumns = model.solver()->getNumCols();
baseSolution_ = new double [numberColumns];
memset(baseSolution_, 0, numberColumns*sizeof(double));
whereFrom_ = 1 + 8 + 255 * 256;
stepSize_ = 0;
k_ = 0;
kmax_ = 0;
nDifferent_ = 0;
}
// Destructor
CbcHeuristicVND::~CbcHeuristicVND ()
{
delete [] baseSolution_;
}
// Clone
CbcHeuristic *
CbcHeuristicVND::clone() const
{
return new CbcHeuristicVND(*this);
}
// Assignment operator
CbcHeuristicVND &
CbcHeuristicVND::operator=( const CbcHeuristicVND & rhs)
{
if (this != &rhs) {
CbcHeuristic::operator=(rhs);
numberSolutions_ = rhs.numberSolutions_;
howOften_ = rhs.howOften_;
numberSuccesses_ = rhs.numberSuccesses_;
numberTries_ = rhs.numberTries_;
lastNode_ = rhs.lastNode_;
delete [] baseSolution_;
if (model_ && rhs.baseSolution_) {
int numberColumns = model_->solver()->getNumCols();
baseSolution_ = new double [numberColumns];
memcpy(baseSolution_, rhs.baseSolution_, numberColumns*sizeof(double));
} else {
baseSolution_ = NULL;
}
stepSize_ = rhs.stepSize_;
k_ = rhs.k_;
kmax_ = rhs.kmax_;
nDifferent_ = rhs.nDifferent_;
}
return *this;
}
// Create C++ lines to get to current state
void
CbcHeuristicVND::generateCpp( FILE * fp)
{
CbcHeuristicVND other;
fprintf(fp, "0#include \"CbcHeuristicVND.hpp\"\n");
fprintf(fp, "3 CbcHeuristicVND heuristicVND(*cbcModel);\n");
CbcHeuristic::generateCpp(fp, "heuristicVND");
if (howOften_ != other.howOften_)
fprintf(fp, "3 heuristicVND.setHowOften(%d);\n", howOften_);
else
fprintf(fp, "4 heuristicVND.setHowOften(%d);\n", howOften_);
fprintf(fp, "3 cbcModel->addHeuristic(&heuristicVND);\n");
}
// Copy constructor
CbcHeuristicVND::CbcHeuristicVND(const CbcHeuristicVND & rhs)
:
CbcHeuristic(rhs),
numberSolutions_(rhs.numberSolutions_),
howOften_(rhs.howOften_),
numberSuccesses_(rhs.numberSuccesses_),
numberTries_(rhs.numberTries_),
lastNode_(rhs.lastNode_)
{
if (model_ && rhs.baseSolution_) {
int numberColumns = model_->solver()->getNumCols();
baseSolution_ = new double [numberColumns];
memcpy(baseSolution_, rhs.baseSolution_, numberColumns*sizeof(double));
} else {
baseSolution_ = NULL;
}
stepSize_ = rhs.stepSize_;
k_ = rhs.k_;
kmax_ = rhs.kmax_;
nDifferent_ = rhs.nDifferent_;
}
// Resets stuff if model changes
void
CbcHeuristicVND::resetModel(CbcModel * /*model*/)
{
//CbcHeuristic::resetModel(model);
delete [] baseSolution_;
if (model_ && baseSolution_) {
int numberColumns = model_->solver()->getNumCols();
baseSolution_ = new double [numberColumns];
memset(baseSolution_, 0, numberColumns*sizeof(double));
} else {
baseSolution_ = NULL;
}
}
/*
First tries setting a variable to better value. If feasible then
tries setting others. If not feasible then tries swaps
Returns 1 if solution, 0 if not */
int
CbcHeuristicVND::solution(double & solutionValue,
double * betterSolution)
{
numCouldRun_++;
int returnCode = 0;
const double * bestSolution = model_->bestSolution();
if (!bestSolution)
return 0; // No solution found yet
if (numberSolutions_ < model_->getSolutionCount()) {
// new solution - add info
numberSolutions_ = model_->getSolutionCount();
int numberIntegers = model_->numberIntegers();
const int * integerVariable = model_->integerVariable();
int i;
for (i = 0; i < numberIntegers; i++) {
int iColumn = integerVariable[i];
const OsiObject * object = model_->object(i);
// get original bounds
double originalLower;
double originalUpper;
getIntegerInformation( object, originalLower, originalUpper);
double value = bestSolution[iColumn];
if (value < originalLower) {
value = originalLower;
} else if (value > originalUpper) {
value = originalUpper;
}
}
}
int numberNodes = model_->getNodeCount();
if (howOften_ == 100) {
if (numberNodes < lastNode_ + 12)
return 0;
// Do at 50 and 100
if ((numberNodes > 40 && numberNodes <= 50) || (numberNodes > 90 && numberNodes < 100))
numberNodes = howOften_;
}
if ((numberNodes % howOften_) == 0 && (model_->getCurrentPassNumber() == 1 ||
model_->getCurrentPassNumber() == 999999)) {
lastNode_ = model_->getNodeCount();
OsiSolverInterface * solver = model_->solver();
int numberIntegers = model_->numberIntegers();
const int * integerVariable = model_->integerVariable();
const double * currentSolution = solver->getColSolution();
OsiSolverInterface * newSolver = cloneBut(3); // was model_->continuousSolver()->clone();
//const double * colLower = newSolver->getColLower();
//const double * colUpper = newSolver->getColUpper();
double primalTolerance;
solver->getDblParam(OsiPrimalTolerance, primalTolerance);
// Sort on distance
double * distance = new double [numberIntegers];
int * which = new int [numberIntegers];
int i;
int nFix = 0;
double tolerance = 10.0 * primalTolerance;
for (i = 0; i < numberIntegers; i++) {
int iColumn = integerVariable[i];
const OsiObject * object = model_->object(i);
// get original bounds
double originalLower;
double originalUpper;
getIntegerInformation( object, originalLower, originalUpper);
double valueInt = bestSolution[iColumn];
if (valueInt < originalLower) {
valueInt = originalLower;
} else if (valueInt > originalUpper) {
valueInt = originalUpper;
}
baseSolution_[iColumn] = currentSolution[iColumn];
distance[i] = fabs(currentSolution[iColumn] - valueInt);
which[i] = i;
if (fabs(currentSolution[iColumn] - valueInt) < tolerance)
nFix++;
}
CoinSort_2(distance, distance + numberIntegers, which);
nDifferent_ = numberIntegers - nFix;
stepSize_ = nDifferent_ / 10;
k_ = stepSize_;
//nFix = numberIntegers-stepSize_;
for (i = 0; i < nFix; i++) {
int j = which[i];
int iColumn = integerVariable[j];
const OsiObject * object = model_->object(i);
// get original bounds
double originalLower;
double originalUpper;
getIntegerInformation( object, originalLower, originalUpper);
double valueInt = bestSolution[iColumn];
if (valueInt < originalLower) {
valueInt = originalLower;
} else if (valueInt > originalUpper) {
valueInt = originalUpper;
}
double nearest = floor(valueInt + 0.5);
newSolver->setColLower(iColumn, nearest);
newSolver->setColUpper(iColumn, nearest);
}
delete [] distance;
delete [] which;
if (nFix > numberIntegers / 5) {
//printf("%d integers have samish value\n",nFix);
returnCode = smallBranchAndBound(newSolver, numberNodes_, betterSolution, solutionValue,
model_->getCutoff(), "CbcHeuristicVND");
if (returnCode < 0)
returnCode = 0; // returned on size
else
numRuns_++;
if ((returnCode&1) != 0)
numberSuccesses_++;
//printf("return code %d",returnCode);
if ((returnCode&2) != 0) {
// could add cut
returnCode &= ~2;
//printf("could add cut with %d elements (if all 0-1)\n",nFix);
} else {
//printf("\n");
}
numberTries_++;
if ((numberTries_ % 10) == 0 && numberSuccesses_*3 < numberTries_)
howOften_ += static_cast<int> (howOften_ * decayFactor_);
}
delete newSolver;
}
return returnCode;
}
// update model
void CbcHeuristicVND::setModel(CbcModel * model)
{
model_ = model;
// Get a copy of original matrix
assert(model_->solver());
delete [] baseSolution_;
int numberColumns = model->solver()->getNumCols();
baseSolution_ = new double [numberColumns];
memset(baseSolution_, 0, numberColumns*sizeof(double));
}