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C++ Reference: class ZeroHalfCutHelper
Note: This documentation is automatically generated.
Heuristic to find a good sums of rows from the LP (with coeff -1, +1) that
can lead to a violated zero-half cut (i.e. after integer rounding with a
divisor 2).
For this, all that matter is the parity of the coefficients and the rhs in
the linear combination of the original problem constraint. So this class
maintain a copy of the LP matrix modulo 2 on which simplification and
heuristic are performed to find good cut candidates(s).
Most of what is done here is described in the paper "Algorithms to Separate
{0, 1/2}-Chvátal-Gomory Cuts", Arie M. C. A. Koster, Adrian Zymolka, Manuel
Kutschka.
| Method |
AddBinaryRow | Return type: void Arguments: const CombinationOfRows& binary_row |
AddOneConstraint | Return type: void Arguments:
glop::RowIndex,
const std::vector<std::pair<glop::ColIndex, IntegerValue>>& terms,
IntegerValue lb, IntegerValue ub |
EliminateVarUsingRow | Return type: void Arguments: int col, int row Visible for testing.
Adds the given row to all other rows having an odd cofficient on the given
column. This then eliminate the entry (col, row) that is now a singleton by
incresing the slack of the given row.
|
InterestingCandidates | Arguments: ModelRandomGenerator* random |
MatrixCol | Return type: const std::vector<int>& Arguments: int col |
MatrixRow | Return type: const CombinationOfRows& Arguments: int row |
ProcessVariables | Return type: void Arguments: const std::vector<double>& lp_values,
const std::vector<IntegerValue>& lower_bounds,
const std::vector<IntegerValue>& upper_bounds Public API: ProcessVariables() must be called first and then constraints
can be added one by one. Finally GetZeroHalfInterestingCuts() will return a
set of good candidates.
TODO(user): This is a first implementation, both the heuristic and the
code performance can probably be improved uppon.
|
Reset | Return type: void Arguments: int size Visible for testing.
|
SymmetricDifference | Return type: void Arguments: std::function<bool(int)> extra_condition,
const std::vector<int>& a, std::vector<int>* b Visible for testing.
Like std::set_symmetric_difference, but use a vector instead of sort.
This assumes tmp_marked_ to be all false. We don't DCHECK it here for
speed, but it DCHECKed on each EliminateVarUsingRow() call. In addition,
the result is filtered using the extra_condition function.
|
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Last updated 2024-08-06 UTC.
[null,null,["Last updated 2024-08-06 UTC."],[],["The `ZeroHalfCutHelper` class aims to find violated zero-half cuts in linear programming. It maintains a copy of the LP matrix modulo 2, focusing on the parity of coefficients and the right-hand side. Key actions include: adding constraints via `AddOneConstraint`, processing variables with `ProcessVariables`, and adding binary rows via `AddBinaryRow`. Other methods include `EliminateVarUsingRow`, `Reset`, `MatrixCol`, `MatrixRow`, `SymmetricDifference`, and `InterestingCandidates`. These methods are designed to simplify and analyze the matrix to discover good cut candidates, according to the heuristic explained in the paper by Arie et al.\n"]]
