Go to the source code of this file.
| #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.
| #define CLP_ABOVE_UPPER 2 |
| #define CLP_METHOD1 ((method_ & 1) != 0) |
| #define CLP_METHOD2 ((method_ & 2) != 0) |
| int originalStatus |
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| int currentStatus |
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| void setOriginalStatus |
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| void setCurrentStatus |
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| void setInitialStatus |
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| void setSameStatus |
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Include dependency graph for ClpNonLinearCost.hpp:
1.8.5
