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experimental support for dynamic loading of gurobi; add MPSolver.CreateSolver() factory method for non C++ languages to check correctly installed linear solver backends and licenses when needed; port all non C++ examples

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This commit is contained in:
Laurent Perron
2020-06-24 18:11:12 +02:00
parent 2f7e8e9eb8
commit d6ecea46ad
42 changed files with 1268 additions and 315 deletions
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61
examples/tests/TestLinearSolver.java
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@@ -50,6 +50,8 @@ public class TestLinearSolver {
logger.info("Advanced usage:");
logger.info("Problem solved in " + solver.wallTime() + " milliseconds");
logger.info("Problem solved in " + solver.iterations() + " iterations");
if (solver.isMip()) return;
vars.forEach(
var-> logger.info(var.name() + ": reduced cost " + var.reducedCost())
);
@@ -62,8 +64,12 @@ public class TestLinearSolver {
);
}
static void runLinearProgrammingExample(MPSolver.OptimizationProblemType problem_type) {
MPSolver solver = new MPSolver("LinearProgrammingExample", problem_type);
static void runLinearProgrammingExample(String problem_type) {
logger.info("------ Linear programming example with " + problem_type + " ------");
MPSolver solver = MPSolver.createSolver("LinearProgrammingExample", problem_type);
if (solver == null) return;
// x and y are continuous non-negative variables.
MPVariable x = solver.makeNumVar(0.0, Double.POSITIVE_INFINITY, "x");
MPVariable y = solver.makeNumVar(0.0, Double.POSITIVE_INFINITY, "y");
@@ -92,8 +98,12 @@ public class TestLinearSolver {
solveAndPrint(solver, new MPVariable[] {x, y}, new MPConstraint[] {c0, c1, c2});
}
static void runMixedIntegerProgrammingExample(MPSolver.OptimizationProblemType problem_type) {
MPSolver solver = new MPSolver("MixedIntegerProgrammingExample", problem_type);
static void runMixedIntegerProgrammingExample(String problem_type) {
logger.info("------ Mixed integer programming example with " + problem_type + " ------");
MPSolver solver = MPSolver.createSolver("MixedIntegerProgrammingExample", problem_type);
if (solver == null) return;
// x and y are continuous non-negative variables.
MPVariable x = solver.makeIntVar(0.0, Double.POSITIVE_INFINITY, "x");
MPVariable y = solver.makeIntVar(0.0, Double.POSITIVE_INFINITY, "y");
@@ -117,8 +127,12 @@ public class TestLinearSolver {
solveAndPrint(solver, new MPVariable[] {x, y}, new MPConstraint[] {c0, c1});
}
static void runBooleanProgrammingExample(MPSolver.OptimizationProblemType problem_type) {
MPSolver solver = new MPSolver("BooleanProgrammingExample", problem_type);
static void runBooleanProgrammingExample(String problem_type) {
logger.info("------ Boolean programming example with " + problem_type + " ------");
MPSolver solver = MPSolver.createSolver("BooleanProgrammingExample", problem_type);
if (solver == null) return;
// x and y are continuous non-negative variables.
MPVariable x = solver.makeBoolVar("x");
MPVariable y = solver.makeBoolVar("y");
@@ -138,9 +152,7 @@ public class TestLinearSolver {
}
static void testSameConstraintName() {
MPSolver solver = new MPSolver(
"My_solver_name",
MPSolver.OptimizationProblemType.CBC_MIXED_INTEGER_PROGRAMMING);
MPSolver solver = MPSolver.createSolver("testSameConstraintName", "CBC");
boolean success = true;
solver.makeConstraint("my_const_name");
try {
@@ -153,8 +165,8 @@ public class TestLinearSolver {
}
static void testSetHintAndSolverGetters() {
MPSolver solver = new MPSolver("testSetHintAndSolverGetters",
MPSolver.OptimizationProblemType.GLOP_LINEAR_PROGRAMMING);
MPSolver solver = MPSolver.createSolver("testSetHintAndSolverGetters", "GLOP");
// x and y are continuous non-negative variables.
MPVariable x = solver.makeIntVar(0.0, Double.POSITIVE_INFINITY, "x");
MPVariable y = solver.makeIntVar(0.0, Double.POSITIVE_INFINITY, "y");
@@ -191,20 +203,17 @@ public class TestLinearSolver {
testSameConstraintName();
testSetHintAndSolverGetters();
MPSolver.OptimizationProblemType problem_types[] = MPSolver.OptimizationProblemType.values();
for (MPSolver.OptimizationProblemType problem_type : problem_types) {
if (problem_type.name().endsWith("LINEAR_PROGRAMMING")) {
logger.info("------ Linear programming example with " + problem_type + " ------");
runLinearProgrammingExample(problem_type);
} else if (problem_type.name().endsWith("MIXED_INTEGER_PROGRAMMING")) {
logger.info("------ Mixed Integer programming example with " + problem_type + " ------");
runMixedIntegerProgrammingExample(problem_type);
} else if (problem_type.name().endsWith("INTEGER_PROGRAMMING")) {
logger.info("------ Boolean programming example with " + problem_type + " ------");
runBooleanProgrammingExample(problem_type);
} else {
logger.severe("Problem type " + problem_type + " unknow !");
}
}
runLinearProgrammingExample("GLOP");
runLinearProgrammingExample("GLPK_LP");
runLinearProgrammingExample("CLP");
runLinearProgrammingExample("GUROBI_LP");
runMixedIntegerProgrammingExample("GLPK");
runMixedIntegerProgrammingExample("CBC");
runMixedIntegerProgrammingExample("SCIP");
runMixedIntegerProgrammingExample("SAT");
runBooleanProgrammingExample("SAT");
runBooleanProgrammingExample("BOP");
}
}