limp-cbc-0.3.2.0: cbits/coin/ClpNonLinearCost.hpp
/* $Id: ClpNonLinearCost.hpp 1769 2011-07-26 09:31:51Z forrest $ */
// Copyright (C) 2002, International Business Machines
// Corporation and others. All Rights Reserved.
// This code is licensed under the terms of the Eclipse Public License (EPL).
#ifndef ClpNonLinearCost_H
#define ClpNonLinearCost_H
#include "CoinPragma.hpp"
class ClpSimplex;
class CoinIndexedVector;
/** Trivial class to deal with non linear costs
I don't make any explicit assumptions about convexity but I am
sure I do make implicit ones.
One interesting idea for normal LP's will be to allow non-basic
variables to come into basis as infeasible i.e. if variable at
lower bound has very large positive reduced cost (when problem
is infeasible) could it reduce overall problem infeasibility more
by bringing it into basis below its lower bound.
Another feature would be to automatically discover when problems
are convex piecewise linear and re-formulate to use non-linear.
I did some work on this many years ago on "grade" problems, but
while it improved primal interior point algorithms were much better
for that particular problem.
*/
/* status has original status and current status
0 - below lower so stored is upper
1 - in range
2 - above upper so stored is lower
4 - (for current) - same as original
*/
#define CLP_BELOW_LOWER 0
#define CLP_FEASIBLE 1
#define CLP_ABOVE_UPPER 2
#define CLP_SAME 4
inline int originalStatus(unsigned char status)
{
return (status & 15);
}
inline int currentStatus(unsigned char status)
{
return (status >> 4);
}
inline void setOriginalStatus(unsigned char & status, int value)
{
status = static_cast<unsigned char>(status & ~15);
status = static_cast<unsigned char>(status | value);
}
inline void setCurrentStatus(unsigned char &status, int value)
{
status = static_cast<unsigned char>(status & ~(15 << 4));
status = static_cast<unsigned char>(status | (value << 4));
}
inline void setInitialStatus(unsigned char &status)
{
status = static_cast<unsigned char>(CLP_FEASIBLE | (CLP_SAME << 4));
}
inline void setSameStatus(unsigned char &status)
{
status = static_cast<unsigned char>(status & ~(15 << 4));
status = static_cast<unsigned char>(status | (CLP_SAME << 4));
}
// Use second version to get more speed
//#define FAST_CLPNON
#ifndef FAST_CLPNON
#define CLP_METHOD1 ((method_&1)!=0)
#define CLP_METHOD2 ((method_&2)!=0)
#else
#define CLP_METHOD1 (false)
#define CLP_METHOD2 (true)
#endif
class ClpNonLinearCost {
public:
public:
/**@name Constructors, destructor */
//@{
/// Default constructor.
ClpNonLinearCost();
/** Constructor from simplex.
This will just set up wasteful arrays for linear, but
later may do dual analysis and even finding duplicate columns .
*/
ClpNonLinearCost(ClpSimplex * model, int method = 1);
/** Constructor from simplex and list of non-linearities (columns only)
First lower of each column has to match real lower
Last lower has to be <= upper (if == then cost ignored)
This could obviously be changed to make more user friendly
*/
ClpNonLinearCost(ClpSimplex * model, const int * starts,
const double * lower, const double * cost);
/// Destructor
~ClpNonLinearCost();
// Copy
ClpNonLinearCost(const ClpNonLinearCost&);
// Assignment
ClpNonLinearCost& operator=(const ClpNonLinearCost&);
//@}
/**@name Actual work in primal */
//@{
/** Changes infeasible costs and computes number and cost of infeas
Puts all non-basic (non free) variables to bounds
and all free variables to zero if oldTolerance is non-zero
- but does not move those <= oldTolerance away*/
void checkInfeasibilities(double oldTolerance = 0.0);
/** Changes infeasible costs for each variable
The indices are row indices and need converting to sequences
*/
void checkInfeasibilities(int numberInArray, const int * index);
/** Puts back correct infeasible costs for each variable
The input indices are row indices and need converting to sequences
for costs.
On input array is empty (but indices exist). On exit just
changed costs will be stored as normal CoinIndexedVector
*/
void checkChanged(int numberInArray, CoinIndexedVector * update);
/** Goes through one bound for each variable.
If multiplier*work[iRow]>0 goes down, otherwise up.
The indices are row indices and need converting to sequences
Temporary offsets may be set
Rhs entries are increased
*/
void goThru(int numberInArray, double multiplier,
const int * index, const double * work,
double * rhs);
/** Takes off last iteration (i.e. offsets closer to 0)
*/
void goBack(int numberInArray, const int * index,
double * rhs);
/** Puts back correct infeasible costs for each variable
The input indices are row indices and need converting to sequences
for costs.
At the end of this all temporary offsets are zero
*/
void goBackAll(const CoinIndexedVector * update);
/// Temporary zeroing of feasible costs
void zapCosts();
/// Refreshes costs always makes row costs zero
void refreshCosts(const double * columnCosts);
/// Puts feasible bounds into lower and upper
void feasibleBounds();
/// Refresh - assuming regions OK
void refresh();
/** Sets bounds and cost for one variable
Returns change in cost
May need to be inline for speed */
double setOne(int sequence, double solutionValue);
/** Sets bounds and infeasible cost and true cost for one variable
This is for gub and column generation etc */
void setOne(int sequence, double solutionValue, double lowerValue, double upperValue,
double costValue = 0.0);
/** Sets bounds and cost for outgoing variable
may change value
Returns direction */
int setOneOutgoing(int sequence, double &solutionValue);
/// Returns nearest bound
double nearest(int sequence, double solutionValue);
/** Returns change in cost - one down if alpha >0.0, up if <0.0
Value is current - new
*/
inline double changeInCost(int sequence, double alpha) const {
double returnValue = 0.0;
if (CLP_METHOD1) {
int iRange = whichRange_[sequence] + offset_[sequence];
if (alpha > 0.0)
returnValue = cost_[iRange] - cost_[iRange-1];
else
returnValue = cost_[iRange] - cost_[iRange+1];
}
if (CLP_METHOD2) {
returnValue = (alpha > 0.0) ? infeasibilityWeight_ : -infeasibilityWeight_;
}
return returnValue;
}
inline double changeUpInCost(int sequence) const {
double returnValue = 0.0;
if (CLP_METHOD1) {
int iRange = whichRange_[sequence] + offset_[sequence];
if (iRange + 1 != start_[sequence+1] && !infeasible(iRange + 1))
returnValue = cost_[iRange] - cost_[iRange+1];
else
returnValue = -1.0e100;
}
if (CLP_METHOD2) {
returnValue = -infeasibilityWeight_;
}
return returnValue;
}
inline double changeDownInCost(int sequence) const {
double returnValue = 0.0;
if (CLP_METHOD1) {
int iRange = whichRange_[sequence] + offset_[sequence];
if (iRange != start_[sequence] && !infeasible(iRange - 1))
returnValue = cost_[iRange] - cost_[iRange-1];
else
returnValue = 1.0e100;
}
if (CLP_METHOD2) {
returnValue = infeasibilityWeight_;
}
return returnValue;
}
/// This also updates next bound
inline double changeInCost(int sequence, double alpha, double &rhs) {
double returnValue = 0.0;
#ifdef NONLIN_DEBUG
double saveRhs = rhs;
#endif
if (CLP_METHOD1) {
int iRange = whichRange_[sequence] + offset_[sequence];
if (alpha > 0.0) {
assert(iRange - 1 >= start_[sequence]);
offset_[sequence]--;
rhs += lower_[iRange] - lower_[iRange-1];
returnValue = alpha * (cost_[iRange] - cost_[iRange-1]);
} else {
assert(iRange + 1 < start_[sequence+1] - 1);
offset_[sequence]++;
rhs += lower_[iRange+2] - lower_[iRange+1];
returnValue = alpha * (cost_[iRange] - cost_[iRange+1]);
}
}
if (CLP_METHOD2) {
#ifdef NONLIN_DEBUG
double saveRhs1 = rhs;
rhs = saveRhs;
#endif
unsigned char iStatus = status_[sequence];
int iWhere = currentStatus(iStatus);
if (iWhere == CLP_SAME)
iWhere = originalStatus(iStatus);
// rhs always increases
if (iWhere == CLP_FEASIBLE) {
if (alpha > 0.0) {
// going below
iWhere = CLP_BELOW_LOWER;
rhs = COIN_DBL_MAX;
} else {
// going above
iWhere = CLP_ABOVE_UPPER;
rhs = COIN_DBL_MAX;
}
} else if (iWhere == CLP_BELOW_LOWER) {
assert (alpha < 0);
// going feasible
iWhere = CLP_FEASIBLE;
rhs += bound_[sequence] - model_->upperRegion()[sequence];
} else {
assert (iWhere == CLP_ABOVE_UPPER);
// going feasible
iWhere = CLP_FEASIBLE;
rhs += model_->lowerRegion()[sequence] - bound_[sequence];
}
setCurrentStatus(status_[sequence], iWhere);
#ifdef NONLIN_DEBUG
assert(saveRhs1 == rhs);
#endif
returnValue = fabs(alpha) * infeasibilityWeight_;
}
return returnValue;
}
/// Returns current lower bound
inline double lower(int sequence) const {
return lower_[whichRange_[sequence] + offset_[sequence]];
}
/// Returns current upper bound
inline double upper(int sequence) const {
return lower_[whichRange_[sequence] + offset_[sequence] + 1];
}
/// Returns current cost
inline double cost(int sequence) const {
return cost_[whichRange_[sequence] + offset_[sequence]];
}
//@}
/**@name Gets and sets */
//@{
/// Number of infeasibilities
inline int numberInfeasibilities() const {
return numberInfeasibilities_;
}
/// Change in cost
inline double changeInCost() const {
return changeCost_;
}
/// Feasible cost
inline double feasibleCost() const {
return feasibleCost_;
}
/// Feasible cost with offset and direction (i.e. for reporting)
double feasibleReportCost() const;
/// Sum of infeasibilities
inline double sumInfeasibilities() const {
return sumInfeasibilities_;
}
/// Largest infeasibility
inline double largestInfeasibility() const {
return largestInfeasibility_;
}
/// Average theta
inline double averageTheta() const {
return averageTheta_;
}
inline void setAverageTheta(double value) {
averageTheta_ = value;
}
inline void setChangeInCost(double value) {
changeCost_ = value;
}
inline void setMethod(int value) {
method_ = value;
}
/// See if may want to look both ways
inline bool lookBothWays() const {
return bothWays_;
}
//@}
///@name Private functions to deal with infeasible regions
inline bool infeasible(int i) const {
return ((infeasible_[i>>5] >> (i & 31)) & 1) != 0;
}
inline void setInfeasible(int i, bool trueFalse) {
unsigned int & value = infeasible_[i>>5];
int bit = i & 31;
if (trueFalse)
value |= (1 << bit);
else
value &= ~(1 << bit);
}
inline unsigned char * statusArray() const {
return status_;
}
/// For debug
void validate();
//@}
private:
/**@name Data members */
//@{
/// Change in cost because of infeasibilities
double changeCost_;
/// Feasible cost
double feasibleCost_;
/// Current infeasibility weight
double infeasibilityWeight_;
/// Largest infeasibility
double largestInfeasibility_;
/// Sum of infeasibilities
double sumInfeasibilities_;
/// Average theta - kept here as only for primal
double averageTheta_;
/// Number of rows (mainly for checking and copy)
int numberRows_;
/// Number of columns (mainly for checking and copy)
int numberColumns_;
/// Starts for each entry (columns then rows)
int * start_;
/// Range for each entry (columns then rows)
int * whichRange_;
/// Temporary range offset for each entry (columns then rows)
int * offset_;
/** Lower bound for each range (upper bound is next lower).
For various reasons there is always an infeasible range
at bottom - even if lower bound is - infinity */
double * lower_;
/// Cost for each range
double * cost_;
/// Model
ClpSimplex * model_;
// Array to say which regions are infeasible
unsigned int * infeasible_;
/// Number of infeasibilities found
int numberInfeasibilities_;
// new stuff
/// Contains status at beginning and current
unsigned char * status_;
/// Bound which has been replaced in lower_ or upper_
double * bound_;
/// Feasible cost array
double * cost2_;
/// Method 1 old, 2 new, 3 both!
int method_;
/// If all non-linear costs convex
bool convex_;
/// If we should look both ways for djs
bool bothWays_;
//@}
};
#endif