#include "CoinPragma.hpp"

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Classes
class	ClpNonLinearCost

Macros
#define	CLP_BELOW_LOWER 0
	Trivial class to deal with non linear costs. More...

#define	CLP_FEASIBLE 1

#define	CLP_ABOVE_UPPER 2

#define	CLP_SAME 4

#define	CLP_METHOD1 ((method_ & 1) != 0)

#define	CLP_METHOD2 ((method_ & 2) != 0)

Functions
int	originalStatus (unsigned char status)

int	currentStatus (unsigned char status)

void	setOriginalStatus (unsigned char &status, int value)

void	setCurrentStatus (unsigned char &status, int value)

void	setInitialStatus (unsigned char &status)

void	setSameStatus (unsigned char &status)

Macro Definition Documentation

#define CLP_BELOW_LOWER 0

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.

Definition at line 37 of file ClpNonLinearCost.hpp.

Referenced by ClpNonLinearCost::changeInCost().

#define CLP_FEASIBLE 1

Definition at line 38 of file ClpNonLinearCost.hpp.

Referenced by ClpNonLinearCost::changeInCost(), and setInitialStatus().

#define CLP_ABOVE_UPPER 2

Definition at line 39 of file ClpNonLinearCost.hpp.

Referenced by ClpNonLinearCost::changeInCost().

#define CLP_SAME 4

Definition at line 40 of file ClpNonLinearCost.hpp.

Referenced by ClpNonLinearCost::changeInCost(), setInitialStatus(), and setSameStatus().

#define CLP_METHOD1 ((method_ & 1) != 0)