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cvrptw_with_resources.cc
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cvrptw_with_resources.cc
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// Copyright 2010-2022 Google LLC
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// Capacitated Vehicle Routing Problem with Time Windows and capacitated
// resources.
// This is an extension to the model in cvrptw.cc so refer to that file for
// more information on the common part of the model. The model implemented here
// limits the number of vehicles which can simultaneously leave or enter the
// depot due to limited resources (or capacity) available.
// TODO(user): The current model consumes resources even for vehicles with
// empty routes; fix this when we have an API on the cumulative constraints
// with variable demands.
#include <cstdint>
#include <vector>
#include "absl/random/random.h"
#include "examples/cpp/cvrptw_lib.h"
#include "google/protobuf/text_format.h"
#include "ortools/base/commandlineflags.h"
#include "ortools/base/init_google.h"
#include "ortools/base/integral_types.h"
#include "ortools/base/logging.h"
#include "ortools/constraint_solver/routing.h"
#include "ortools/constraint_solver/routing_index_manager.h"
#include "ortools/constraint_solver/routing_parameters.h"
#include "ortools/constraint_solver/routing_parameters.pb.h"
using operations_research::Assignment;
using operations_research::DefaultRoutingSearchParameters;
using operations_research::GetSeed;
using operations_research::IntervalVar;
using operations_research::IntVar;
using operations_research::LocationContainer;
using operations_research::RandomDemand;
using operations_research::RoutingDimension;
using operations_research::RoutingIndexManager;
using operations_research::RoutingModel;
using operations_research::RoutingNodeIndex;
using operations_research::RoutingSearchParameters;
using operations_research::ServiceTimePlusTransition;
using operations_research::Solver;
ABSL_FLAG(int, vrp_orders, 100, "Nodes in the problem.");
ABSL_FLAG(int, vrp_vehicles, 20,
"Size of Traveling Salesman Problem instance.");
ABSL_FLAG(bool, vrp_use_deterministic_random_seed, false,
"Use deterministic random seeds.");
ABSL_FLAG(std::string, routing_search_parameters, "",
"Text proto RoutingSearchParameters (possibly partial) that will "
"override the DefaultRoutingSearchParameters()");
const char* kTime = "Time";
const char* kCapacity = "Capacity";
int main(int argc, char** argv) {
InitGoogle(argv[0], &argc, &argv, true);
CHECK_LT(0, absl::GetFlag(FLAGS_vrp_orders))
<< "Specify an instance size greater than 0.";
CHECK_LT(0, absl::GetFlag(FLAGS_vrp_vehicles))
<< "Specify a non-null vehicle fleet size.";
// VRP of size absl::GetFlag(FLAGS_vrp_size).
// Nodes are indexed from 0 to absl::GetFlag(FLAGS_vrp_orders), the starts and
// ends of the routes are at node 0.
const RoutingIndexManager::NodeIndex kDepot(0);
RoutingIndexManager manager(absl::GetFlag(FLAGS_vrp_orders) + 1,
absl::GetFlag(FLAGS_vrp_vehicles), kDepot);
RoutingModel routing(manager);
// Setting up locations.
const int64_t kXMax = 100000;
const int64_t kYMax = 100000;
const int64_t kSpeed = 10;
LocationContainer locations(
kSpeed, absl::GetFlag(FLAGS_vrp_use_deterministic_random_seed));
for (int location = 0; location <= absl::GetFlag(FLAGS_vrp_orders);
++location) {
locations.AddRandomLocation(kXMax, kYMax);
}
// Setting the cost function.
const int vehicle_cost = routing.RegisterTransitCallback(
[&locations, &manager](int64_t i, int64_t j) {
return locations.ManhattanDistance(manager.IndexToNode(i),
manager.IndexToNode(j));
});
routing.SetArcCostEvaluatorOfAllVehicles(vehicle_cost);
// Adding capacity dimension constraints.
const int64_t kVehicleCapacity = 40;
const int64_t kNullCapacitySlack = 0;
RandomDemand demand(manager.num_nodes(), kDepot,
absl::GetFlag(FLAGS_vrp_use_deterministic_random_seed));
demand.Initialize();
routing.AddDimension(routing.RegisterTransitCallback(
[&demand, &manager](int64_t i, int64_t j) {
return demand.Demand(manager.IndexToNode(i),
manager.IndexToNode(j));
}),
kNullCapacitySlack, kVehicleCapacity,
/*fix_start_cumul_to_zero=*/true, kCapacity);
// Adding time dimension constraints.
const int64_t kTimePerDemandUnit = 300;
const int64_t kHorizon = 24 * 3600;
ServiceTimePlusTransition time(
kTimePerDemandUnit,
[&demand](RoutingNodeIndex i, RoutingNodeIndex j) {
return demand.Demand(i, j);
},
[&locations](RoutingNodeIndex i, RoutingNodeIndex j) {
return locations.ManhattanTime(i, j);
});
routing.AddDimension(
routing.RegisterTransitCallback([&time, &manager](int64_t i, int64_t j) {
return time.Compute(manager.IndexToNode(i), manager.IndexToNode(j));
}),
kHorizon, kHorizon, /*fix_start_cumul_to_zero=*/false, kTime);
const RoutingDimension& time_dimension = routing.GetDimensionOrDie(kTime);
// Adding time windows.
std::mt19937 randomizer(
GetSeed(absl::GetFlag(FLAGS_vrp_use_deterministic_random_seed)));
const int64_t kTWDuration = 5 * 3600;
for (int order = 1; order < manager.num_nodes(); ++order) {
const int64_t start =
absl::Uniform<int32_t>(randomizer, 0, kHorizon - kTWDuration);
time_dimension.CumulVar(order)->SetRange(start, start + kTWDuration);
}
// Adding resource constraints at the depot (start and end location of
// routes).
std::vector<IntVar*> start_end_times;
for (int i = 0; i < absl::GetFlag(FLAGS_vrp_vehicles); ++i) {
start_end_times.push_back(time_dimension.CumulVar(routing.End(i)));
start_end_times.push_back(time_dimension.CumulVar(routing.Start(i)));
}
// Build corresponding time intervals.
const int64_t kVehicleSetup = 180;
Solver* const solver = routing.solver();
std::vector<IntervalVar*> intervals;
solver->MakeFixedDurationIntervalVarArray(start_end_times, kVehicleSetup,
"depot_interval", &intervals);
// Constrain the number of maximum simultaneous intervals at depot.
const int64_t kDepotCapacity = 5;
std::vector<int64_t> depot_usage(start_end_times.size(), 1);
solver->AddConstraint(
solver->MakeCumulative(intervals, depot_usage, kDepotCapacity, "depot"));
// Instantiate route start and end times to produce feasible times.
for (int i = 0; i < start_end_times.size(); ++i) {
routing.AddVariableMinimizedByFinalizer(start_end_times[i]);
}
// Adding penalty costs to allow skipping orders.
const int64_t kPenalty = 100000;
const RoutingIndexManager::NodeIndex kFirstNodeAfterDepot(1);
for (RoutingIndexManager::NodeIndex order = kFirstNodeAfterDepot;
order < manager.num_nodes(); ++order) {
std::vector<int64_t> orders(1, manager.NodeToIndex(order));
routing.AddDisjunction(orders, kPenalty);
}
// Solve, returns a solution if any (owned by RoutingModel).
RoutingSearchParameters parameters = DefaultRoutingSearchParameters();
CHECK(google::protobuf::TextFormat::MergeFromString(
absl::GetFlag(FLAGS_routing_search_parameters), ¶meters));
const Assignment* solution = routing.SolveWithParameters(parameters);
if (solution != nullptr) {
DisplayPlan(manager, routing, *solution, /*use_same_vehicle_costs=*/false,
/*max_nodes_per_group=*/0, /*same_vehicle_cost=*/0,
routing.GetDimensionOrDie(kCapacity),
routing.GetDimensionOrDie(kTime));
} else {
LOG(INFO) << "No solution found.";
}
return EXIT_SUCCESS;
}