Google OR-Tools v9.11
a fast and portable software suite for combinatorial optimization
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#include <solution_feasibility_checker.h>
Public Attributes | |
double | absolute_constraint_tolerance = 1.0e-6 |
double | integrality_tolerance = 1.0e-5 |
double | nonzero_tolerance = 1.0e-5 |
Definition at line 25 of file solution_feasibility_checker.h.
double operations_research::math_opt::FeasibilityCheckerOptions::absolute_constraint_tolerance = 1.0e-6 |
Used for evaluating the feasibility of primal solution values with respect to linear constraints and variable bounds.
For example, variable values x are considered feasible with respect to a constraint <a, x> ≤ b iff <a, x> ≤ b + absolute_constraint_tolerance.
Cannot be negative or NaN.
Definition at line 33 of file solution_feasibility_checker.h.
double operations_research::math_opt::FeasibilityCheckerOptions::integrality_tolerance = 1.0e-5 |
An absolute tolerance used for evaluating the feasibility of a variable's value with respect to integrality constraints on that variable, if present.
For example, a value x for an integer variable is considered feasible with respect to its integrality constraints iff |x - round(x)| ≤ integrality_tolerance.
Cannot be negative or NaN.
Definition at line 43 of file solution_feasibility_checker.h.
double operations_research::math_opt::FeasibilityCheckerOptions::nonzero_tolerance = 1.0e-5 |
Absolute tolerance for evaluating if an expression is sufficiently close to a particular value (usually zero, hence the name).
This is used for evaluating if SOS1 and SOS2 constraints are satisfied, as well as for evaluating indicator constraint feasibility (i.e., is the indicator variable at its "activation value").
For example, variable values x are considered feasible with respect to an SOS1 constraint {expr_1(x), ..., expr_d(x)}-is-SOS1 iff there is at most one j such that |expr_j(x)| > nonzero_tolerance.
Cannot be negative or NaN.
Definition at line 57 of file solution_feasibility_checker.h.