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backport linear_solver, math_opt, pdlp and util from main

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This commit is contained in:
Corentin Le Molgat
2024-03-25 11:54:18 +01:00
parent 2b0085be7d
commit c9b1ad998a
62 changed files with 1141 additions and 395 deletions
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2
ortools/linear_solver/samples/BUILD.bazel
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@@ -28,6 +28,8 @@ code_sample_cc(name = "mip_var_array")
code_sample_cc(name = "multiple_knapsack_mip")
#code_sample_cc(name = "network_design_ilph")
code_sample_cc(name = "simple_lp_program")
code_sample_cc(name = "simple_mip_program")

36
ortools/linear_solver/samples/BasicExample.cs
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@@ -15,6 +15,7 @@
// [START program]
// [START import]
using System;
using Google.OrTools.Init;
using Google.OrTools.LinearSolver;
// [END import]
@@ -22,11 +23,14 @@ public class BasicExample
{
static void Main()
{
Console.WriteLine("Google.OrTools version: " + OrToolsVersion.VersionString());
// [START solver]
// Create the linear solver with the GLOP backend.
Solver solver = Solver.CreateSolver("GLOP");
if (solver is null)
{
Console.WriteLine("Could not create solver GLOP");
return;
}
// [END solver]
@@ -40,10 +44,10 @@ public class BasicExample
// [END variables]
// [START constraints]
// Create a linear constraint, 0 <= x + y <= 2.
Constraint ct = solver.MakeConstraint(0.0, 2.0, "ct");
ct.SetCoefficient(x, 1);
ct.SetCoefficient(y, 1);
// Create a linear constraint, x + y <= 2.
Constraint constraint = solver.MakeConstraint(double.NegativeInfinity, 2.0, "constraint");
constraint.SetCoefficient(x, 1);
constraint.SetCoefficient(y, 1);
Console.WriteLine("Number of constraints = " + solver.NumConstraints());
// [END constraints]
@@ -57,15 +61,37 @@ public class BasicExample
// [END objective]
// [START solve]
solver.Solve();
Console.WriteLine("Solving with " + solver.SolverVersion());
Solver.ResultStatus resultStatus = solver.Solve();
// [END solve]
// [START print_solution]
Console.WriteLine("Status: " + resultStatus);
if (resultStatus != Solver.ResultStatus.OPTIMAL)
{
Console.WriteLine("The problem does not have an optimal solution!");
if (resultStatus == Solver.ResultStatus.FEASIBLE)
{
Console.WriteLine("A potentially suboptimal solution was found");
}
else
{
Console.WriteLine("The solver could not solve the problem.");
return;
}
}
Console.WriteLine("Solution:");
Console.WriteLine("Objective value = " + solver.Objective().Value());
Console.WriteLine("x = " + x.SolutionValue());
Console.WriteLine("y = " + y.SolutionValue());
// [END print_solution]
// [START advanced]
Console.WriteLine("Advanced usage:");
Console.WriteLine("Problem solved in " + solver.WallTime() + " milliseconds");
Console.WriteLine("Problem solved in " + solver.Iterations() + " iterations");
// [END advanced]
}
}
// [END program]

36
ortools/linear_solver/samples/BasicExample.java
View File

@@ -14,8 +14,10 @@
// Minimal example to call the GLOP solver.
// [START program]
package com.google.ortools.linearsolver.samples;
// [START import]
import com.google.ortools.Loader;
import com.google.ortools.init.OrToolsVersion;
import com.google.ortools.linearsolver.MPConstraint;
import com.google.ortools.linearsolver.MPObjective;
import com.google.ortools.linearsolver.MPSolver;
@@ -25,10 +27,19 @@ import com.google.ortools.linearsolver.MPVariable;
/** Minimal Linear Programming example to showcase calling the solver. */
public final class BasicExample {
public static void main(String[] args) {
// [START loader]
Loader.loadNativeLibraries();
// [END loader]
System.out.println("Google OR-Tools version: " + OrToolsVersion.getVersionString());
// [START solver]
// Create the linear solver with the GLOP backend.
MPSolver solver = MPSolver.createSolver("GLOP");
if (solver == null) {
System.out.println("Could not create solver GLOP");
return;
}
// [END solver]
// [START variables]
@@ -40,8 +51,9 @@ public final class BasicExample {
// [END variables]
// [START constraints]
// Create a linear constraint, 0 <= x + y <= 2.
MPConstraint ct = solver.makeConstraint(0.0, 2.0, "ct");
double infinity = Double.POSITIVE_INFINITY;
// Create a linear constraint, x + y <= 2.
MPConstraint ct = solver.makeConstraint(-infinity, 2.0, "ct");
ct.setCoefficient(x, 1);
ct.setCoefficient(y, 1);
@@ -57,15 +69,33 @@ public final class BasicExample {
// [END objective]
// [START solve]
solver.solve();
System.out.println("Solving with " + solver.solverVersion());
final MPSolver.ResultStatus resultStatus = solver.solve();
// [END solve]
// [START print_solution]
System.out.println("Status: " + resultStatus);
if (resultStatus != MPSolver.ResultStatus.OPTIMAL) {
System.out.println("The problem does not have an optimal solution!");
if (resultStatus == MPSolver.ResultStatus.FEASIBLE) {
System.out.println("A potentially suboptimal solution was found");
} else {
System.out.println("The solver could not solve the problem.");
return;
}
}
System.out.println("Solution:");
System.out.println("Objective value = " + objective.value());
System.out.println("x = " + x.solutionValue());
System.out.println("y = " + y.solutionValue());
// [END print_solution]
// [START advanced]
System.out.println("Advanced usage:");
System.out.println("Problem solved in " + solver.wallTime() + " milliseconds");
System.out.println("Problem solved in " + solver.iterations() + " iterations");
// [END advanced]
}
private BasicExample() {}

47
ortools/linear_solver/samples/basic_example.cc
View File

@@ -11,20 +11,31 @@
// See the License for the specific language governing permissions and
// limitations under the License.
// Minimal example to call the GLOP solver.
// [START program]
// Minimal example to call the GLOP solver.
// [START import]
#include <cstdlib>
#include <memory>
#include <ostream>
#include "absl/flags/flag.h"
#include "absl/log/flags.h"
#include "ortools/base/init_google.h"
#include "ortools/base/logging.h"
#include "ortools/init/init.h"
#include "ortools/linear_solver/linear_solver.h"
// [END import]
namespace operations_research {
void BasicExample() {
LOG(INFO) << "Google OR-Tools version : " << OrToolsVersion::VersionString();
// [START solver]
// Create the linear solver with the GLOP backend.
std::unique_ptr<MPSolver> solver(MPSolver::CreateSolver("GLOP"));
if (!solver) {
LOG(WARNING) << "Could not create solver GLOP";
return;
}
// [END solver]
// [START variables]
@@ -36,8 +47,9 @@ void BasicExample() {
// [END variables]
// [START constraints]
// Create a linear constraint, 0 <= x + y <= 2.
MPConstraint* const ct = solver->MakeRowConstraint(0.0, 2.0, "ct");
// Create a linear constraint, x + y <= 2.
const double infinity = solver->infinity();
MPConstraint* const ct = solver->MakeRowConstraint(-infinity, 2.0, "ct");
ct->SetCoefficient(x, 1);
ct->SetCoefficient(y, 1);
@@ -53,19 +65,40 @@ void BasicExample() {
// [END objective]
// [START solve]
solver->Solve();
LOG(INFO) << "Solving with " << solver->SolverVersion();
const MPSolver::ResultStatus result_status = solver->Solve();
// [END solve]
// [START print_solution]
LOG(INFO) << "Solution:" << std::endl;
// Check that the problem has an optimal solution.
LOG(INFO) << "Status: " << result_status;
if (result_status != MPSolver::OPTIMAL) {
LOG(INFO) << "The problem does not have an optimal solution!";
if (result_status == MPSolver::FEASIBLE) {
LOG(INFO) << "A potentially suboptimal solution was found";
} else {
LOG(WARNING) << "The solver could not solve the problem.";
return;
}
}
LOG(INFO) << "Solution:";
LOG(INFO) << "Objective value = " << objective->Value();
LOG(INFO) << "x = " << x->solution_value();
LOG(INFO) << "y = " << y->solution_value();
// [END print_solution]
// [START advanced]
LOG(INFO) << "Advanced usage:";
LOG(INFO) << "Problem solved in " << solver->wall_time() << " milliseconds";
LOG(INFO) << "Problem solved in " << solver->iterations() << " iterations";
// [END advanced]
}
} // namespace operations_research
int main() {
int main(int argc, char* argv[]) {
InitGoogle(argv[0], &argc, &argv, true);
absl::SetFlag(&FLAGS_stderrthreshold, 0);
operations_research::BasicExample();
return EXIT_SUCCESS;
}

47
ortools/linear_solver/samples/basic_example.py
View File

@@ -15,31 +15,36 @@
"""Minimal example to call the GLOP solver."""
# [START program]
# [START import]
from ortools.init.python import init
from ortools.linear_solver import pywraplp
# [END import]
def main():
print("Google OR-Tools version:", init.OrToolsVersion.version_string())
# [START solver]
# Create the linear solver with the GLOP backend.
solver = pywraplp.Solver.CreateSolver("GLOP")
if not solver:
print("Could not create solver GLOP")
return
# [END solver]
# [START variables]
# Create the variables x and y.
x = solver.NumVar(0, 1, "x")
y = solver.NumVar(0, 2, "y")
x_var = solver.NumVar(0, 1, "x")
y_var = solver.NumVar(0, 2, "y")
print("Number of variables =", solver.NumVariables())
# [END variables]
# [START constraints]
# Create a linear constraint, 0 <= x + y <= 2.
ct = solver.Constraint(0, 2, "ct")
ct.SetCoefficient(x, 1)
ct.SetCoefficient(y, 1)
infinity = solver.infinity()
# Create a linear constraint, x + y <= 2.
constraint = solver.Constraint(-infinity, 2, "ct")
constraint.SetCoefficient(x_var, 1)
constraint.SetCoefficient(y_var, 1)
print("Number of constraints =", solver.NumConstraints())
# [END constraints]
@@ -47,24 +52,44 @@ def main():
# [START objective]
# Create the objective function, 3 * x + y.
objective = solver.Objective()
objective.SetCoefficient(x, 3)
objective.SetCoefficient(y, 1)
objective.SetCoefficient(x_var, 3)
objective.SetCoefficient(y_var, 1)
objective.SetMaximization()
# [END objective]
# [START solve]
print(f"Solving with {solver.SolverVersion()}")
solver.Solve()
result_status = solver.Solve()
# [END solve]
# [START print_solution]
print(f"Status: {result_status}")
if result_status != pywraplp.Solver.OPTIMAL:
print("The problem does not have an optimal solution!")
if result_status == pywraplp.Solver.FEASIBLE:
print("A potentially suboptimal solution was found")
else:
print("The solver could not solve the problem.")
return
print("Solution:")
print("Objective value =", objective.Value())
print("x =", x.solution_value())
print("y =", y.solution_value())
print("x =", x_var.solution_value())
print("y =", y_var.solution_value())
# [END print_solution]
# [START advanced]
print("Advanced usage:")
print(f"Problem solved in {solver.wall_time():d} milliseconds")
print(f"Problem solved in {solver.iterations():d} iterations")
# [END advanced]
if __name__ == "__main__":
init.CppBridge.init_logging("basic_example.py")
cpp_flags = init.CppFlags()
cpp_flags.stderrthreshold = True
cpp_flags.log_prefix = False
init.CppBridge.set_flags(cpp_flags)
main()
# [END program]

5
ortools/linear_solver/samples/code_samples.bzl
View File

@@ -21,6 +21,7 @@ def code_sample_cc(name):
srcs = [name + ".cc"],
deps = [
"//ortools/base",
"//ortools/init",
"//ortools/linear_solver",
"//ortools/linear_solver:linear_solver_cc_proto",
],
@@ -33,6 +34,7 @@ def code_sample_cc(name):
deps = [
":" + name + "_cc",
"//ortools/base",
"//ortools/init",
"//ortools/linear_solver",
"//ortools/linear_solver:linear_solver_cc_proto",
],
@@ -48,6 +50,7 @@ def code_sample_py(name):
requirement("protobuf"),
requirement("numpy"),
requirement("pandas"),
"//ortools/init/python:init",
"//ortools/linear_solver/python:model_builder",
],
python_version = "PY3",
@@ -60,6 +63,7 @@ def code_sample_py(name):
srcs = [name + ".py"],
main = name + ".py",
data = [
"//ortools/init/python:init",
"//ortools/linear_solver/python:model_builder",
],
deps = [
@@ -80,6 +84,7 @@ def code_sample_java(name):
main_class = "com.google.ortools.linearsolver.samples." + name,
test_class = "com.google.ortools.linearsolver.samples." + name,
deps = [
"//ortools/init/java:init",
"//ortools/linear_solver/java:modelbuilder",
"//ortools/java/com/google/ortools/modelbuilder",
"//ortools/java/com/google/ortools:Loader",