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Merge branch 'main' of github.com:google/or-tools

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This commit is contained in:
Laurent Perron
2025-02-28 18:09:32 +01:00
parent e343956c6d 854a038027
commit f244e28cbf
5 changed files with 88 additions and 76 deletions
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3
examples/cpp/multi_knapsack_sat.cc
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@@ -20,6 +20,7 @@
// of each items.
#include <cstdint>
#include <cstdlib>
#include <string>
#include <vector>
@@ -32,7 +33,7 @@
ABSL_FLAG(int, size, 16, "scaling factor of the model");
ABSL_FLAG(std::string, params,
"num_workers:8,log_search_progress:true,max_time_in_seconds:10.0",
"num_workers:8,log_search_progress:false,max_time_in_seconds:10.0",
"Sat parameters");
namespace operations_research {
namespace sat {

22
examples/cpp/pdptw.cc
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@@ -83,8 +83,7 @@ ABSL_FLAG(std::string, routing_model_parameters, "",
"Text proto RoutingModelParameters (possibly partial) that will "
"override the DefaultRoutingModelParameters()");
namespace operations_research {
namespace routing {
namespace operations_research::routing {
namespace {
// Returns the list of variables to use for the Tabu metaheuristic.
@@ -131,7 +130,7 @@ double ComputeScalingFactorFromCallback(const C& callback, int size) {
void SetupModel(const LiLimParser& parser, const RoutingIndexManager& manager,
RoutingModel* model,
routing::RoutingSearchParameters* search_parameters) {
RoutingSearchParameters* search_parameters) {
const int64_t kPenalty = 100000000;
const int64_t kFixedCost = 100000;
const int num_nodes = parser.NumberOfNodes();
@@ -357,24 +356,25 @@ bool LoadAndSolve(absl::string_view pdp_file,
return false;
}
} // namespace routing
} // namespace operations_research
} // namespace operations_research::routing
namespace o_r = ::operations_research::routing;
int main(int argc, char** argv) {
absl::SetStderrThreshold(absl::LogSeverityAtLeast::kInfo);
InitGoogle(argv[0], &argc, &argv, true);
operations_research::routing::RoutingModelParameters model_parameters =
operations_research::routing::DefaultRoutingModelParameters();
o_r::RoutingModelParameters model_parameters =
o_r::DefaultRoutingModelParameters();
model_parameters.set_reduce_vehicle_cost_model(
absl::GetFlag(FLAGS_reduce_vehicle_cost_model));
CHECK(google::protobuf::TextFormat::MergeFromString(
absl::GetFlag(FLAGS_routing_model_parameters), &model_parameters));
operations_research::routing::RoutingSearchParameters search_parameters =
operations_research::routing::DefaultRoutingSearchParameters();
o_r::RoutingSearchParameters search_parameters =
o_r::DefaultRoutingSearchParameters();
CHECK(google::protobuf::TextFormat::MergeFromString(
absl::GetFlag(FLAGS_routing_search_parameters), &search_parameters));
if (!operations_research::routing::LoadAndSolve(
absl::GetFlag(FLAGS_pdp_file), model_parameters, search_parameters)) {
if (!o_r::LoadAndSolve(absl::GetFlag(FLAGS_pdp_file), model_parameters,
search_parameters)) {
LOG(INFO) << "Error solving " << absl::GetFlag(FLAGS_pdp_file);
}
return EXIT_SUCCESS;

11
examples/cpp/random_tsp.cc
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@@ -25,14 +25,22 @@
// (forbidden arcs).
#include <cstdint>
#include <cstdlib>
#include <memory>
#include <random>
#include <string>
#include "absl/base/log_severity.h"
#include "absl/flags/flag.h"
#include "absl/flags/parse.h"
#include "absl/log/check.h"
#include "absl/log/globals.h"
#include "absl/log/initialize.h"
#include "absl/log/log.h"
#include "absl/random/random.h"
#include "absl/strings/str_cat.h"
#include "google/protobuf/text_format.h"
#include "ortools/constraint_solver/constraint_solver.h"
#include "ortools/routing/index_manager.h"
#include "ortools/routing/parameters.h"
#include "ortools/routing/parameters.pb.h"
@@ -182,6 +190,9 @@ void Tsp() {
} // namespace operations_research::routing
int main(int argc, char** argv) {
absl::InitializeLog();
absl::EnableLogPrefix(false);
absl::SetStderrThreshold(absl::LogSeverityAtLeast::kInfo);
absl::ParseCommandLine(argc, argv);
operations_research::routing::Tsp();
return EXIT_SUCCESS;

126
examples/java/CapacitatedVehicleRoutingProblemWithTimeWindows.java
View File

@@ -30,21 +30,6 @@ import java.util.function.LongBinaryOperator;
import java.util.function.LongUnaryOperator;
import java.util.logging.Logger;
// A pair class
class Pair<K, V> {
final K first;
final V second;
public static <K, V> Pair<K, V> of(K element0, V element1) {
return new Pair<K, V>(element0, element1);
}
public Pair(K element0, V element1) {
this.first = element0;
this.second = element1;
}
}
/**
* Sample showing how to model and solve a capacitated vehicle routing problem with time windows
* using the swig-wrapped version of the vehicle routing library in
@@ -54,82 +39,97 @@ public class CapacitatedVehicleRoutingProblemWithTimeWindows {
private static final Logger logger =
Logger.getLogger(CapacitatedVehicleRoutingProblemWithTimeWindows.class.getName());
// A pair class
static class Pair<K, V> {
final K first;
final V second;
public static <K, V> Pair<K, V> of(K element0, V element1) {
return new Pair<K, V>(element0, element1);
}
public Pair(K element0, V element1) {
this.first = element0;
this.second = element1;
}
}
static class DataModel {
// Locations representing either an order location or a vehicle route
// start/end.
// Locations representing either an order location or a vehicle route
// start/end.
public final List<Pair<Integer, Integer>> locations = new ArrayList<>();
// Quantity to be picked up for each order.
// Quantity to be picked up for each order.
public final List<Integer> orderDemands = new ArrayList<>();
// Time window in which each order must be performed.
// Time window in which each order must be performed.
public final List<Pair<Integer, Integer>> orderTimeWindows = new ArrayList<>();
// Penalty cost "paid" for dropping an order.
// Penalty cost "paid" for dropping an order.
public final List<Integer> orderPenalties = new ArrayList<>();
public final int numberOfVehicles = 20;
// Capacity of the vehicles.
// Capacity of the vehicles.
public final int vehicleCapacity = 50;
public final int numberOfOrders = 100;
// Latest time at which each vehicle must end its tour.
// Latest time at which each vehicle must end its tour.
public final List<Integer> vehicleEndTime = new ArrayList<>();
// Cost per unit of distance of each vehicle.
// Cost per unit of distance of each vehicle.
public final List<Integer> vehicleCostCoefficients = new ArrayList<>();
// Vehicle start and end indices. They have to be implemented as int[] due
// to the available SWIG-ed interface.
// Vehicle start and end indices. They have to be implemented as int[] due
// to the available SWIG-ed interface.
public int[] vehicleStarts;
public int[] vehicleEnds;
// Random number generator to produce data.
private final Random randomGenerator = new Random(0xBEEF);
// Random number generator to produce data.
private final Random randomGenerator = new Random(0xBEEF);
/**
/**
* Creates order data. Location of the order is random, as well as its demand (quantity), time
* window and penalty.
*
* @param xMax maximum x coordinate in which orders are located.
* @param yMax maximum y coordinate in which orders are located.
* @param demandMax maximum quantity of a demand.
* @param timeWindowMax maximum starting time of the order time window.
* @param timeWindowWidth duration of the order time window.
* @param penaltyMin minimum pernalty cost if order is dropped.
* @param penaltyMax maximum pernalty cost if order is dropped.
*/
*
* @param xMax maximum x coordinate in which orders are located.
* @param yMax maximum y coordinate in which orders are located.
* @param demandMax maximum quantity of a demand.
* @param timeWindowMax maximum starting time of the order time window.
* @param timeWindowWidth duration of the order time window.
* @param penaltyMin minimum pernalty cost if order is dropped.
* @param penaltyMax maximum pernalty cost if order is dropped.
*/
private void buildOrders(int xMax, int yMax, int demandMax, int timeWindowMax,
int timeWindowWidth, int penaltyMin, int penaltyMax) {
for (int order = 0; order < numberOfOrders; ++order) {
for (int order = 0; order < numberOfOrders; ++order) {
locations.add(
Pair.of(randomGenerator.nextInt(xMax + 1), randomGenerator.nextInt(yMax + 1)));
orderDemands.add(randomGenerator.nextInt(demandMax + 1));
int timeWindowStart = randomGenerator.nextInt(timeWindowMax + 1);
orderTimeWindows.add(Pair.of(timeWindowStart, timeWindowStart + timeWindowWidth));
orderPenalties.add(randomGenerator.nextInt(penaltyMax - penaltyMin + 1) + penaltyMin);
orderDemands.add(randomGenerator.nextInt(demandMax + 1));
int timeWindowStart = randomGenerator.nextInt(timeWindowMax + 1);
orderTimeWindows.add(Pair.of(timeWindowStart, timeWindowStart + timeWindowWidth));
orderPenalties.add(randomGenerator.nextInt(penaltyMax - penaltyMin + 1) + penaltyMin);
}
}
}
/**
/**
* Creates fleet data. Vehicle starting and ending locations are random, as well as vehicle
* costs per distance unit.
*
* @param xMax maximum x coordinate in which orders are located.
* @param yMax maximum y coordinate in which orders are located.
* @param endTime latest end time of a tour of a vehicle.
*
* @param xMax maximum x coordinate in which orders are located.
* @param yMax maximum y coordinate in which orders are located.
* @param endTime latest end time of a tour of a vehicle.
* @param costCoefficientMax maximum cost per distance unit of a vehicle (minimum is 1),
*/
*/
private void buildFleet(int xMax, int yMax, int endTime, int costCoefficientMax) {
vehicleStarts = new int[numberOfVehicles];
vehicleEnds = new int[numberOfVehicles];
for (int vehicle = 0; vehicle < numberOfVehicles; ++vehicle) {
vehicleStarts[vehicle] = locations.size();
vehicleStarts = new int[numberOfVehicles];
vehicleEnds = new int[numberOfVehicles];
for (int vehicle = 0; vehicle < numberOfVehicles; ++vehicle) {
vehicleStarts[vehicle] = locations.size();
locations.add(
Pair.of(randomGenerator.nextInt(xMax + 1), randomGenerator.nextInt(yMax + 1)));
vehicleEnds[vehicle] = locations.size();
vehicleEnds[vehicle] = locations.size();
locations.add(
Pair.of(randomGenerator.nextInt(xMax + 1), randomGenerator.nextInt(yMax + 1)));
vehicleEndTime.add(endTime);
vehicleCostCoefficients.add(randomGenerator.nextInt(costCoefficientMax) + 1);
vehicleEndTime.add(endTime);
vehicleCostCoefficients.add(randomGenerator.nextInt(costCoefficientMax) + 1);
}
}
}
public DataModel() {
final int xMax = 20;
@@ -174,7 +174,7 @@ public class CapacitatedVehicleRoutingProblemWithTimeWindows {
};
}
/// @brief Print the solution.
// Print the solution.
static void printSolution(
DataModel data, RoutingModel model, RoutingIndexManager manager, Assignment solution) {
RoutingSearchStatus.Value status = model.status();
@@ -184,7 +184,6 @@ public class CapacitatedVehicleRoutingProblemWithTimeWindows {
logger.warning("No solution found!");
return;
}
String output = "";
// Solution cost.
logger.info("Objective : " + solution.objectiveValue());
@@ -196,7 +195,7 @@ public class CapacitatedVehicleRoutingProblemWithTimeWindows {
}
}
if (dropped.length() > 0) {
output += "Dropped orders:" + dropped + "\n";
logger.info("Dropped orders:" + dropped);
}
// Routes
@@ -221,12 +220,12 @@ public class CapacitatedVehicleRoutingProblemWithTimeWindows {
IntVar time = timeDimension.cumulVar(index);
long nodeIndex = manager.indexToNode(index);
route += nodeIndex + " Load(" + solution.value(load) + ")";
route += " Time(" + solution.min(time) + ", " + solution.max(time) + ") -> ";
route += " Time(" + solution.min(time) + ", " + solution.max(time) + ")";
logger.info(route);
}
}
public static void main(String[] args) throws Exception {
public static void main(String[] args) {
Loader.loadNativeLibraries();
// Instantiate the data problem.
@@ -261,7 +260,6 @@ public class CapacitatedVehicleRoutingProblemWithTimeWindows {
};
unused = model.addDimension(model.registerUnaryTransitCallback(demandCallback), 0,
data.vehicleCapacity, true, "capacity");
RoutingDimension capacityDimension = model.getMutableDimension("capacity");
// Setting up vehicles
LongBinaryOperator[] callbacks = new LongBinaryOperator[data.numberOfVehicles];
@@ -293,4 +291,6 @@ public class CapacitatedVehicleRoutingProblemWithTimeWindows {
// Print solution on console.
printSolution(data, model, manager, solution);
}
private CapacitatedVehicleRoutingProblemWithTimeWindows() {}
}

2
examples/java/LinearProgramming.java
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@@ -79,7 +79,7 @@ public class LinearProgramming {
// Verify that the solution satisfies all constraints (when using solvers
// others than GLOP_LINEAR_PROGRAMMING, this is highly recommended!).
if (!solver.verifySolution(/*tolerance=*/1e-7, /*log_errors=*/true)) {
if (!solver.verifySolution(/* tolerance= */ 1e-7, /* log_errors= */ true)) {
System.err.println("The solution returned by the solver violated the"
+ " problem constraints by at least 1e-7");
return;