| Package | Description |
|---|---|
| com.google.ortools.constraintsolver |
| Modifier and Type | Method and Description |
|---|---|
protected static long |
SWIGTYPE_p_std__vectorT_bool_t.getCPtr(SWIGTYPE_p_std__vectorT_bool_t obj) |
SolutionCollector |
Solver.MakeBestLexicographicValueSolutionCollector(Assignment assignment,
SWIGTYPE_p_std__vectorT_bool_t maximize)
Same as above, but supporting lexicographic objectives; 'maximize'
specifies the optimization direction for each objective in 'assignment'. |
SolutionCollector |
Solver.MakeBestLexicographicValueSolutionCollector(SWIGTYPE_p_std__vectorT_bool_t maximize)
Same as above, but supporting lexicographic objectives; 'maximize'
specifies the optimization direction for each objective. |
ImprovementSearchLimit |
Solver.MakeLexicographicImprovementLimit(IntVar[] objective_vars,
SWIGTYPE_p_std__vectorT_bool_t maximize,
double[] objective_scaling_factors,
double[] objective_offsets,
double improvement_rate_coefficient,
int improvement_rate_solutions_distance)
Same as MakeImprovementLimit on a lexicographic objective based on
'objective_vars' and related arguments. |
OptimizeVar |
Solver.MakeLexicographicOptimize(SWIGTYPE_p_std__vectorT_bool_t maximize,
IntVar[] variables,
long[] steps)
Creates a lexicographic objective, following the order of the variables
given. |
ObjectiveMonitor |
Solver.MakeLexicographicSimulatedAnnealing(SWIGTYPE_p_std__vectorT_bool_t maximize,
IntVar[] vars,
long[] steps,
long[] initial_temperatures) |
ObjectiveMonitor |
Solver.MakeLexicographicTabuSearch(SWIGTYPE_p_std__vectorT_bool_t maximize,
IntVar[] objectives,
long[] steps,
IntVar[] vars,
long keep_tenure,
long forbid_tenure,
double tabu_factor) |
SolutionCollector |
Solver.MakeNBestLexicographicValueSolutionCollector(Assignment assignment,
int solution_count,
SWIGTYPE_p_std__vectorT_bool_t maximize)
Same as above but supporting lexicographic objectives; 'maximize'
specifies the optimization direction for each objective. |
SolutionCollector |
Solver.MakeNBestLexicographicValueSolutionCollector(int solution_count,
SWIGTYPE_p_std__vectorT_bool_t maximize) |
protected static long |
SWIGTYPE_p_std__vectorT_bool_t.swigRelease(SWIGTYPE_p_std__vectorT_bool_t obj) |
| Constructor and Description |
|---|
ImprovementSearchLimit(Solver solver,
IntVar[] objective_vars,
SWIGTYPE_p_std__vectorT_bool_t maximize,
double[] objective_scaling_factors,
double[] objective_offsets,
double improvement_rate_coefficient,
int improvement_rate_solutions_distance) |
ObjectiveMonitor(Solver solver,
SWIGTYPE_p_std__vectorT_bool_t maximize,
IntVar[] vars,
long[] steps) |
OptimizeVar(Solver solver,
SWIGTYPE_p_std__vectorT_bool_t maximize,
IntVar[] vars,
long[] steps) |
Copyright © 2024. All rights reserved.