public void SimpleLambdaCallback(bool callGC)
{
// Create Routing Index Manager
RoutingIndexManager manager = new RoutingIndexManager(
5 /*locations*/, 1 /*vehicle*/, 0 /*depot*/);
// Create Routing Model.
RoutingModel routing = new RoutingModel(manager);
// Create a distance callback.
int transitCallbackIndex = routing.RegisterTransitCallback(
(long fromIndex, long toIndex) => {
// Convert from routing variable Index to distance matrix NodeIndex.
var fromNode = manager.IndexToNode(fromIndex);
var toNode = manager.IndexToNode(toIndex);
return(Math.Abs(toNode - fromNode));
});
// Define cost of each arc.
routing.SetArcCostEvaluatorOfAllVehicles(transitCallbackIndex);
if (callGC)
{
GC.Collect();
}
// Setting first solution heuristic.
RoutingSearchParameters searchParameters =
operations_research_constraint_solver.DefaultRoutingSearchParameters();
searchParameters.FirstSolutionStrategy =
FirstSolutionStrategy.Types.Value.PathCheapestArc;
Assignment solution = routing.SolveWithParameters(searchParameters);
// 0 --(+1)-> 1 --(+1)-> 2 --(+1)-> 3 --(+1)-> 4 --(+4)-> 0 := +8
Assert.Equal(8, solution.ObjectiveValue());
}
public void TestVectorDimension()
{
// Create Routing Index Manager
RoutingIndexManager manager = new RoutingIndexManager(5 /*locations*/, 1 /*vehicle*/, 0 /*depot*/);
// Create Routing Model.
RoutingModel routing = new RoutingModel(manager);
// Create a distance callback.
long[] vector = new long[] { 1, 1, 1, 1, 1 };
IntBoolPair result = routing.AddVectorDimension(
vector,
/*capacity=*/ 10,
/*fix_start_cumul_to_zero=*/ true,
"Dimension");
// Define cost of each arc.
routing.SetArcCostEvaluatorOfAllVehicles(result.first);
// Setting first solution heuristic.
RoutingSearchParameters searchParameters =
operations_research_constraint_solver.DefaultRoutingSearchParameters();
searchParameters.FirstSolutionStrategy = FirstSolutionStrategy.Types.Value.PathCheapestArc;
Assignment solution = routing.SolveWithParameters(searchParameters);
// 0 --(+1)-> 1 --(+1)-> 2 --(+1)-> 3 --(+1)-> 4 --(+1)-> 0 := +5
Assert.Equal(5, solution.ObjectiveValue());
}
public void TestTransitMatrix()
{
// Create Routing Index Manager
RoutingIndexManager manager = new RoutingIndexManager(5 /*locations*/, 1 /*vehicle*/, 0 /*depot*/);
// Create Routing Model.
RoutingModel routing = new RoutingModel(manager);
// Create a distance callback.
long[][] matrix = new long[][] {
new long[] { 1, 1, 1, 1, 1 },
new long[] { 1, 1, 1, 1, 1 },
new long[] { 1, 1, 1, 1, 1 },
new long[] { 1, 1, 1, 1, 1 },
new long[] { 1, 1, 1, 1, 1 },
};
int transitCallbackIndex = routing.RegisterTransitMatrix(matrix);
// Define cost of each arc.
routing.SetArcCostEvaluatorOfAllVehicles(transitCallbackIndex);
// Setting first solution heuristic.
RoutingSearchParameters searchParameters =
operations_research_constraint_solver.DefaultRoutingSearchParameters();
searchParameters.FirstSolutionStrategy = FirstSolutionStrategy.Types.Value.PathCheapestArc;
Assignment solution = routing.SolveWithParameters(searchParameters);
// 0 --(+1)-> 1 --(+1)-> 2 --(+1)-> 3 --(+1)-> 4 --(+1)-> 0 := +5
Assert.Equal(5, solution.ObjectiveValue());
}
public Assignment TryGetSolution(RoutingSearchParameters searchParameters)
{
Assignment solution = null;
if (searchParameters == null)
{
searchParameters = GetDefaultSearchParameters();
}
//for loop that tries to find the earliest feasible solution (trying to minimize the maximum upper bound) within a maximum delay delivery time (upper bound), using the current customer requests
for (int currentMaximumDelayTime = 0; currentMaximumDelayTime < DataModel.MaxAllowedDeliveryDelayTime; currentMaximumDelayTime = currentMaximumDelayTime + 60) //iterates adding 1 minute to maximum allowed timeWindow (60 seconds) if a feasible solution isnt found for the current upperbound
{
MaximumDeliveryDelayTime = currentMaximumDelayTime;
Init();
//Get the solution of the problem
try
{
solution = RoutingModel.SolveWithParameters(searchParameters);
}
catch (Exception)
{
solution = null;
}
if (solution != null) //if true, solution was found, breaks the cycle
{
break;
}
}
Console.WriteLine("Solver status:" + GetSolverStatus());
return(solution); //retuns null if no solution is found, otherwise returns the solution
}
public static int[] Run(long[] DistanceMatrix, int num, int VehicleNumber, int Depot, RoutingSearchParameters searchParameters)
{
// Instantiate the data problem.
// Create Routing Index Manager
RoutingIndexManager manager = new RoutingIndexManager(
num,
VehicleNumber,
Depot);
// Create Routing Model.
RoutingModel routing = new RoutingModel(manager);
int transitCallbackIndex = routing.RegisterTransitCallback(
(long fromIndex, long toIndex) => {
// Convert from routing variable Index to distance matrix NodeIndex.
var fromNode = manager.IndexToNode(fromIndex);
var toNode = manager.IndexToNode(toIndex);
return(DistanceMatrix[fromNode * num + toNode]);
}
);
// Define cost of each arc.
routing.SetArcCostEvaluatorOfAllVehicles(transitCallbackIndex);
// Solve the problem.
Assignment solution = routing.SolveWithParameters(searchParameters);
// Print solution on console.
return(GetOrder(routing, manager, solution));
}
static void Solve(int size, int forbidden, int seed)
{
RoutingIndexManager manager = new RoutingIndexManager(size, 1, 0);
RoutingModel routing = new RoutingModel(manager);
// Setting the cost function.
// Put a permanent callback to the distance accessor here. The callback
// has the following signature: ResultCallback2<int64_t, int64_t, int64_t>.
// The two arguments are the from and to node inidices.
RandomManhattan distances = new RandomManhattan(manager, size, seed);
routing.SetArcCostEvaluatorOfAllVehicles(routing.RegisterTransitCallback(distances.Call));
// Forbid node connections (randomly).
Random randomizer = new Random();
long forbidden_connections = 0;
while (forbidden_connections < forbidden)
{
long from = randomizer.Next(size - 1);
long to = randomizer.Next(size - 1) + 1;
if (routing.NextVar(from).Contains(to))
{
Console.WriteLine("Forbidding connection {0} -> {1}", from, to);
routing.NextVar(from).RemoveValue(to);
++forbidden_connections;
}
}
// Add dummy dimension to test API.
routing.AddDimension(routing.RegisterUnaryTransitCallback((long index) =>
{ return(1); }),
size + 1, size + 1, true, "dummy");
// Solve, returns a solution if any (owned by RoutingModel).
RoutingSearchParameters search_parameters =
operations_research_constraint_solver.DefaultRoutingSearchParameters();
// Setting first solution heuristic (cheapest addition).
search_parameters.FirstSolutionStrategy = FirstSolutionStrategy.Types.Value.PathCheapestArc;
Assignment solution = routing.SolveWithParameters(search_parameters);
Console.WriteLine("Status = {0}", routing.GetStatus());
if (solution != null)
{
// Solution cost.
Console.WriteLine("Cost = {0}", solution.ObjectiveValue());
// Inspect solution.
// Only one route here; otherwise iterate from 0 to routing.vehicles() - 1
int route_number = 0;
for (long node = routing.Start(route_number); !routing.IsEnd(node);
node = solution.Value(routing.NextVar(node)))
{
Console.Write("{0} -> ", node);
}
Console.WriteLine("0");
}
}
/// <summary>
/// Print the solution.
/// </summary>
static void VRP_LongestSingleRoute()
{
Console.WriteLine("VRP_LongestSingleRoute!");
// Instantiate the data problem.
ORDataModel data = new ORDataModel();
// public RoutingIndexManager(int num_nodes, int num_vehicles, int depot);
//public RoutingIndexManager(int num_nodes, int num_vehicles, int[] starts, int[] ends);
// Create Routing Index Manager
RoutingIndexManager manager = new RoutingIndexManager(
data.DistanceMatrix.GetLength(0),
data.VehicleNumber,
data.Depot);
// Create Routing Model.
RoutingModel routing = new RoutingModel(manager);
// Create and register a transit callback.
int transitCallbackIndex = routing.RegisterTransitCallback(
(long fromIndex, long toIndex) => {
// Convert from routing variable Index to distance matrix NodeIndex.
var fromNode = manager.IndexToNode(fromIndex);
var toNode = manager.IndexToNode(toIndex);
return(data.DistanceMatrix[fromNode, toNode]);
}
);
// Define cost of each arc.
routing.SetArcCostEvaluatorOfAllVehicles(transitCallbackIndex);
// Add Distance constraint.
routing.AddDimension(transitCallbackIndex, 0, 3000,
true, // start cumul to zero
"Distance");
RoutingDimension distanceDimension = routing.GetMutableDimension("Distance");
distanceDimension.SetGlobalSpanCostCoefficient(100);
// Setting first solution heuristic.
RoutingSearchParameters searchParameters =
operations_research_constraint_solver.DefaultRoutingSearchParameters();
searchParameters.FirstSolutionStrategy =
FirstSolutionStrategy.Types.Value.PathCheapestArc;
// Solve the problem.
Assignment solution = routing.SolveWithParameters(searchParameters);
// Print solution on console.
PrintSolutionPathCheapest(data, routing, manager, solution);
}
private void Distancia()
{
long routeDistance = 0;
RoutingSearchParameters searchParameters =
operations_research_constraint_solver.DefaultRoutingSearchParameters();
searchParameters.FirstSolutionStrategy = FirstSolutionStrategy.Types.Value.PathCheapestArc;
DataModel data = new DataModel(Distancias, 1, 0);
RoutingIndexManager manager = new RoutingIndexManager(
data.DistanceMatrix.GetLength(0),
data.VehicleNumber,
data.Depot);
RoutingModel routing = new RoutingModel(manager);
int transitCallbackIndex = routing.RegisterTransitCallback(
(long fromIndex, long toIndex) => {
// Convert from routing variable Index to distance matrix NodeIndex.
var fromNode = manager.IndexToNode(fromIndex);
var toNode = manager.IndexToNode(toIndex);
return(data.DistanceMatrix[fromNode, toNode]);
});
routing.SetArcCostEvaluatorOfAllVehicles(transitCallbackIndex);
Assignment solution = routing.SolveWithParameters(searchParameters);
var index = routing.Start(0);
int indice = 1;
string CadenaR = "";
string c = "";
while (routing.IsEnd(index) == false)
{
//Recorrido[indice] = manager.IndexToNode((int)index);
c = manager.IndexToNode((int)index).ToString();
CadenaR = CadenaR + " - " + c;
var previousIndex = index;
index = solution.Value(routing.NextVar(index));
routeDistance += routing.GetArcCostForVehicle(previousIndex, index, 0);
indice++;
}
//Recorrido[indice] = manager.IndexToNode((int)index);
c = manager.IndexToNode((int)index).ToString();
CadenaR = CadenaR + " - " + c;
Km = routeDistance;
CadenaRecorrido = CadenaR;
}
public FileOutput Solve(FileInput input, RoutingSearchParameters searchParameters)
{
WorkData data = converter.ToWorkData(input);
RoutingIndexManager manager = new RoutingIndexManager(data.DistanceMatrix.GetLength(0), data.VehiclesAmount, data.Starts, data.Ends);
RoutingModel routing = new RoutingModel(manager);
AddCapacityConstrains(data, manager, routing);
AddTimeWindowConstrains(data, manager, routing);
AddPenaltiesAndDroppingVisits(data, manager, routing);
Assignment solution = routing.SolveWithParameters(searchParameters);
if (solution == null)
{
return(null);
}
return(converter.ConvertToFileOutput(input, manager, routing, solution));
}
/// <summary>
/// Print the solution.
/// </summary>
public static int[] Solve()
{
int[] result = new int[200];
int cnt = 0;
// Create Routing Index Manager
RoutingIndexManager manager = new RoutingIndexManager(Ranks, VehicleNumber, Depot);
// Create Routing Model.
RoutingModel routing = new RoutingModel(manager);
int transitCallbackIndex = routing.RegisterTransitCallback(
(long fromIndex, long toIndex) => {
// Convert from routing variable Index to distance matrix NodeIndex.
var fromNode = manager.IndexToNode(fromIndex);
var toNode = manager.IndexToNode(toIndex);
return((long)distMat[fromNode, toNode]);
}
);
routing.SetArcCostEvaluatorOfAllVehicles(transitCallbackIndex);
// Setting first solution heuristic.
RoutingSearchParameters searchParameters =
operations_research_constraint_solver.DefaultRoutingSearchParameters();
searchParameters.FirstSolutionStrategy =
FirstSolutionStrategy.Types.Value.PathCheapestArc;
// Solve the problem.
Assignment solution = routing.SolveWithParameters(searchParameters);
// Inspect solution.
var index = routing.Start(0);
while (routing.IsEnd(index) == false)
{
result[cnt++] = Convert.ToInt32(index);
var previousIndex = index;
index = solution.Value(routing.NextVar(index));
}
return(result);
}
public string[] Solve(string[] nodes)
{
var routing = new RoutingModel(nodes.Length, 1, 0);
routing.SetCost(new HaversineDistanceEvaluator(nodes, _maps));
var parameters = RoutingModel.DefaultSearchParameters();
parameters.FirstSolutionStrategy = FirstSolutionStrategy.Types.Value.PathCheapestArc;
var solution = routing.SolveWithParameters(parameters);
int routeNumber = 0;
var results = new List <string>();
for (long node = routing.Start(routeNumber); !routing.IsEnd(node); node = solution.Value(routing.NextVar(node)))
{
results.Add(nodes[routing.IndexToNode(node)]);
}
return(results.ToArray());
}
public List <Destination> SolveTsp(List <Destination> destinations)
{
var tspSize = destinations.Count;
// One route because there is one traveller:
var numberOfRoutes = 1;
// The homet town is inserted at position 0 in the list, so the "depot" index is 0:
var depotIndex = 0;
// Compose the model:
var model = new RoutingModel(tspSize, numberOfRoutes, depotIndex);
// Setup search params
var searchParameters = RoutingModel.DefaultSearchParameters();
// Find a first solution with the cheapest addition algorithm:
searchParameters.FirstSolutionStrategy = FirstSolutionStrategy.Types.Value.PathCheapestArc;
// Use GLS for local search metaheuristic:
searchParameters.LocalSearchMetaheuristic = LocalSearchMetaheuristic.Types.Value.GuidedLocalSearch;
// Lower valuest make the local search more fine-grained
searchParameters.GuidedLocalSearchLambdaCoefficient = 0.1;
// The calculations are given one second to perform:
searchParameters.TimeLimitMs = 1000;
//Setup arc costs evaluation:
var arcCostEvaluator = new DistanceCallback(destinations.Select(d => new Point {
X = d.X, Y = d.Y
}).ToList());
model.SetArcCostEvaluatorOfAllVehicles(arcCostEvaluator);
// Solve the problem:
var solution = model.SolveWithParameters(searchParameters);
if (solution != null)
{
return(ExtractWaybillsFromSolution(solution, model, destinations));
}
return(new List <Destination>());
}
/// <summary>
/// Solves the current routing problem.
/// </summary>
private void Solve(int number_of_orders, int number_of_vehicles)
{
Console.WriteLine("Creating model with " + number_of_orders + " orders and " + number_of_vehicles +
" vehicles.");
// Finalizing model
int number_of_locations = locations_.Length;
RoutingIndexManager manager =
new RoutingIndexManager(number_of_locations, number_of_vehicles, vehicle_starts_, vehicle_ends_);
RoutingModel model = new RoutingModel(manager);
// Setting up dimensions
const int big_number = 100000;
Manhattan manhattan_callback = new Manhattan(manager, locations_, 1);
model.AddDimension(model.RegisterTransitCallback(manhattan_callback.Call), big_number, big_number, false,
"time");
RoutingDimension time_dimension = model.GetDimensionOrDie("time");
Demand demand_callback = new Demand(manager, order_demands_);
model.AddDimension(model.RegisterUnaryTransitCallback(demand_callback.Call), 0, vehicle_capacity_, true,
"capacity");
RoutingDimension capacity_dimension = model.GetDimensionOrDie("capacity");
// Setting up vehicles
Manhattan[] cost_callbacks = new Manhattan[number_of_vehicles];
for (int vehicle = 0; vehicle < number_of_vehicles; ++vehicle)
{
int cost_coefficient = vehicle_cost_coefficients_[vehicle];
Manhattan manhattan_cost_callback = new Manhattan(manager, locations_, cost_coefficient);
cost_callbacks[vehicle] = manhattan_cost_callback;
int manhattan_cost_index = model.RegisterTransitCallback(manhattan_cost_callback.Call);
model.SetArcCostEvaluatorOfVehicle(manhattan_cost_index, vehicle);
time_dimension.CumulVar(model.End(vehicle)).SetMax(vehicle_end_time_[vehicle]);
}
// Setting up orders
for (int order = 0; order < number_of_orders; ++order)
{
time_dimension.CumulVar(order).SetRange(order_time_windows_[order].start_, order_time_windows_[order].end_);
long[] orders = { manager.NodeToIndex(order) };
model.AddDisjunction(orders, order_penalties_[order]);
}
// Solving
RoutingSearchParameters search_parameters =
operations_research_constraint_solver.DefaultRoutingSearchParameters();
search_parameters.FirstSolutionStrategy = FirstSolutionStrategy.Types.Value.AllUnperformed;
Console.WriteLine("Search...");
Assignment solution = model.SolveWithParameters(search_parameters);
if (solution != null)
{
String output = "Total cost: " + solution.ObjectiveValue() + "\n";
// Dropped orders
String dropped = "";
for (int order = 0; order < number_of_orders; ++order)
{
if (solution.Value(model.NextVar(order)) == order)
{
dropped += " " + order;
}
}
if (dropped.Length > 0)
{
output += "Dropped orders:" + dropped + "\n";
}
// Routes
for (int vehicle = 0; vehicle < number_of_vehicles; ++vehicle)
{
String route = "Vehicle " + vehicle + ": ";
long order = model.Start(vehicle);
if (model.IsEnd(solution.Value(model.NextVar(order))))
{
route += "Empty";
}
else
{
for (; !model.IsEnd(order); order = solution.Value(model.NextVar(order)))
{
IntVar local_load = capacity_dimension.CumulVar(order);
IntVar local_time = time_dimension.CumulVar(order);
route += order + " Load(" + solution.Value(local_load) + ") " + "Time(" +
solution.Min(local_time) + ", " + solution.Max(local_time) + ") -> ";
}
IntVar load = capacity_dimension.CumulVar(order);
IntVar time = time_dimension.CumulVar(order);
route += order + " Load(" + solution.Value(load) + ") " + "Time(" + solution.Min(time) + ", " +
solution.Max(time) + ")";
}
output += route + "\n";
}
Console.WriteLine(output);
}
}
//IntVar x;
//IntVar y;//Reduntant
public void SolveVrpProblem(Day day, ConfigParams cfg, VrpProblem vrpProblem, IDataOutput dataOutput, int[] VCMinMax)
{
this.day = day;
this.cfg = cfg;
//Google Distance Matrix API (Duration matrix)
// Create Routing Index Manager
manager = new RoutingIndexManager(
day.TimeMatrix.GetLength(0),
day.Vehicles.Count,
day.Depot);
// Create Routing Model.
routing = new RoutingModel(manager);
// Create and register a transit callback.
int transitCallbackIndex = routing.RegisterTransitCallback(
(long fromIndex, long toIndex) =>
{
// Convert from routing variable Index to distance matrix NodeIndex.
var fromNode = manager.IndexToNode(fromIndex);
var toNode = manager.IndexToNode(toIndex);
return(day.TimeMatrix[fromNode, toNode]);
}
);
// Define cost of each arc.
routing.SetArcCostEvaluatorOfAllVehicles(transitCallbackIndex);
// Add Distance constraint.
if (day.TimeWindowsActive != true)
{
routing.AddDimension(transitCallbackIndex, 0, 700000,
true, // start cumul to zero
"Distance");
RoutingDimension distanceDimension = routing.GetMutableDimension("Distance");
distanceDimension.SetGlobalSpanCostCoefficient(100);
}
else
{
routing.AddDimension(
transitCallbackIndex, // transit callback
1000, // allow waiting time
600, // vehicle maximum capacities
false, // start cumul to zero
"Time");
TimeWindowInit(day, routing, manager);//Set Time Window Constraints
}
if (day.MaxVisitsActive != 0)
{
int demandCallbackIndex = routing.RegisterUnaryTransitCallback(
(long fromIndex) => {
// Convert from routing variable Index to demand NodeIndex.
var fromNode = manager.IndexToNode(fromIndex);
return(day.Demands[fromNode]);
}
);
routing.AddDimensionWithVehicleCapacity(
demandCallbackIndex, 0, // null capacity slack
day.VehicleCapacities, // vehicle maximum capacities
true, // start cumul to zero
"Capacity");
}
// Allow to drop nodes.
for (int i = 1; i < day.TimeMatrix.GetLength(0); ++i)
{
routing.AddDisjunction(
new long[] { manager.NodeToIndex(i) }, day.Locations.ElementAt(i).Penalty);
}
// Setting first solution heuristic.
RoutingSearchParameters searchParameters =
operations_research_constraint_solver.DefaultRoutingSearchParameters();
searchParameters.FirstSolutionStrategy =
FirstSolutionStrategy.Types.Value.PathMostConstrainedArc;
//metaheuristic
searchParameters.LocalSearchMetaheuristic = LocalSearchMetaheuristic.Types.Value.GuidedLocalSearch;
searchParameters.TimeLimit = new Duration {
Seconds = cfg.SolutionDuration
};
searchParameters.LogSearch = true;
solver = routing.solver();
//TODO
//Some location must be on same route.
//solver.Add(routing.VehicleVar(manager.NodeToIndex(2)) == routing.VehicleVar(manager.NodeToIndex(5)));
//One node takes precedence over the another.
//routing.AddPickupAndDelivery(manager.NodeToIndex(2), manager.NodeToIndex(5));
//Constraint variable
//x = solver.MakeIntVar(day.Vehicles.Count, day.Vehicles.Count, "x");
//Number of vehicle restriction - old version
//solver.Add(x < 7);
//Number of vehicle restriction -new version
//y = solver.MakeIntVar(routing.Vehicles(), routing.Vehicles(), "y");
//solver.Add(y <= VCMinMax[1]);//Reduntant
// Solve the problem.
solution = routing.SolveWithParameters(searchParameters);
day.LocationDropped = false;
// Display dropped nodes.
List <int> droppedNodes = new List <int>();
for (int index = 0; index < routing.Size(); ++index)
{
if (routing.IsStart(index) || routing.IsEnd(index))
{
continue;
}
if (solution.Value(routing.NextVar(index)) == index)
{
droppedNodes.Add(manager.IndexToNode((int)index));
day.LocationDropped = true;
}
}
day.DroppedLocations.Clear();
Console.WriteLine(day.Locations.ElementAt(0).Name);
if (droppedNodes != null)
{
foreach (var item in droppedNodes)
{
Location location = LocationDB.Locations.Where(x => x.Position.strPos_ == day.Addresses[item]).ToList().ElementAt(0);
if (location != null)
{
Console.WriteLine(location.Name);
day.DroppedLocations.Add(location);
}
}
}
List <int> AssignedNodes = new List <int>();
Console.WriteLine(manager.GetNumberOfNodes());
//Inspect Infeasable Nodes
for (int i = 0; i < day.Vehicles.Count; i++)
{
var index = routing.Start(i);
int j = 0;
while (routing.IsEnd(index) == false)
{
j++;
index = solution.Value(routing.NextVar(index));
}
if (j == 1)
{
day.InfeasibleNodes = true;
foreach (var item in day.DroppedLocations)
{
LocationDB.Locations.Where(x => x.ClientRef == item.ClientRef).ToList().ElementAt(0).Infeasible = true;
}
if (day.Vehicles.Count - 1 >= 1)
{
day.SetVehicleNumber(day.Vehicles.Count - 1);
day.ResetResults();
vrpProblem.SolveVrpProblem(day, cfg, vrpProblem, dataOutput, VCMinMax);
}
return;
}
}
// Inspect solution.
day.TotalDur = 0;
day.MinDur = 100000;
for (int i = 0; i < day.Vehicles.Count; i++)
{
long routeDuration = 0;
var index = routing.Start(i);
while (routing.IsEnd(index) == false)
{
var previousIndex = index;
index = solution.Value(routing.NextVar(index));
routeDuration += routing.GetArcCostForVehicle(previousIndex, index, 0);
}
day.TotalDur += routeDuration;
day.MaxDur = Math.Max(routeDuration, day.MaxDur);
day.MinDur = Math.Min(routeDuration, day.MinDur);
}
day.AvgDur = day.TotalDur / day.Vehicles.Count;
}
static void Main(string[] args)
{
List <string> Addresses = new List <string>()
{
"New York", "Los Angeles", "Chicago", "Minneapolis",
"Denver", "Dallas", "Seattle", "Boston", "San Francisco", "St.Louis",
"Houston", "Phoenix", "Salt Lake City"
};
APIGoogle.Register("AIzaSyCkYDMEPLWCFvq3Oi-LJyEsMuh_06Fk62g");
List <LatLng> listLatLng = new List <LatLng>();
foreach (string item in Addresses)
{
listLatLng.Add(APIGoogle.GetLatLng(item));
}
DirectionRequest directionRequest = new DirectionRequest();
DirectionService directionService = new DirectionService();
long[,] CityDistanceMatrix = new long[Addresses.Count, Addresses.Count];
for (int i = 0; i < Addresses.Count; i++)
{
for (int j = 0; j < Addresses.Count; j++)
{
directionRequest.Origin = Addresses[i];
directionRequest.Sensor = false;
{
directionRequest.Destination = Addresses[j];
var ttt = directionService.GetResponse(directionRequest);
CityDistanceMatrix[i, j] = directionService.GetResponse(directionRequest).Routes[0].Legs[0].Distance.Value / 1000;
};
}
}
int NumRoutes = 1; // The number of routes, which is 1 in the TSP.
// Nodes are indexed from 0 to tsp_size - 1. The depot is the starting node of the route.
int Depot = 0;
int TspSize = Addresses.Count;
if (TspSize > 0)
{
RoutingModel routing = new RoutingModel(TspSize, NumRoutes, Depot);
RoutingSearchParameters search_parameters = RoutingModel.DefaultSearchParameters();
CityDistance dist_between_nodes = new CityDistance(CityDistanceMatrix, Addresses);
routing.SetArcCostEvaluatorOfAllVehicles(dist_between_nodes);
//routing.SetCost(dist_between_nodes);
Demand demands_at_locations = new Demand(new int[] { 1, 2, 3, 4, 5, 6, 7, 8, 9 });
search_parameters.FirstSolutionStrategy = FirstSolutionStrategy.Types.Value.PathCheapestArc;
Assignment solution = routing.SolveWithParameters(search_parameters);
Console.WriteLine("Status = {0}", routing.Status());
if (solution != null)
{
// Solution cost.
Console.WriteLine("Suma [km]= {0}", solution.ObjectiveValue() / 1000);
// Inspect solution.
// Only one route here; otherwise iterate from 0 to routing.vehicles() - 1
int route_number = 0;
for (long node = routing.Start(route_number);
!routing.IsEnd(node);
node = solution.Value(routing.NextVar(node)))
{
Console.Write("{0} \n", Addresses[(int)node]);
}
Console.WriteLine(Addresses[0]);
}
}
Console.ReadKey();
}
/// <summary>
/// Solves the current routing problem.
/// </summary>
static void Solve()
{
// Instantiate the data problem.
// [START data]
const int num_location = 5;
const int num_vehicles = 1;
const int depot = 0;
// [END data]
// Create Routing Index Manager
// [START index_manager]
RoutingIndexManager manager = new RoutingIndexManager(num_location, num_vehicles, depot);
// [END index_manager]
// Create Routing Model.
// [START routing_model]
RoutingModel routing = new RoutingModel(manager);
// [END routing_model]
// Define cost of each arc.
// [START arc_cost]
routing.SetArcCostEvaluatorOfAllVehicles(
routing.RegisterTransitCallback(
(long FromIndex, long ToIndex) => {
return(1L);
}
));
// [END arc_cost]
// Setting first solution heuristic.
// [START parameters]
RoutingSearchParameters searchParameters =
operations_research_constraint_solver.DefaultRoutingSearchParameters();
searchParameters.FirstSolutionStrategy =
FirstSolutionStrategy.Types.Value.PathCheapestArc;
// [END parameters]
// Solve the problem.
// [START solve]
Assignment solution = routing.SolveWithParameters(searchParameters);
// [END solve]
// Print solution on console.
// [START print_solution]
Console.WriteLine("Objective: {0}", solution.ObjectiveValue());
// Inspect solution.
long index = routing.Start(0);
Console.WriteLine("Route for Vehicle 0:");
long route_distance = 0;
while (routing.IsEnd(index) == false)
{
Console.Write("{0} -> ", manager.IndexToNode((int)index));
long previousIndex = index;
index = solution.Value(routing.NextVar(index));
route_distance += routing.GetArcCostForVehicle(previousIndex, index, 0);
}
Console.WriteLine("{0}", manager.IndexToNode(index));
Console.WriteLine("Distance of the route: {0}m", route_distance);
// [END print_solution]
}
public IList <string> GetShortestOptimizedRoute([FromBody] GeographicViewModel geographicVM)
{
// double[] latitude = { 13.121329, 13.065150, 13.024346, 13.027691, 12.913887, 12.915754, 12.962431, 12.890461, 12.907220, 12.954234, 13.026996, 13.041044, 13.001573 };
//double[] longitude = { 80.029049, 80.128613, 79.909573, 80.259762, 80.253067, 80.192041, 80.253839, 80.097198, 80.142088, 80.188437, 80.107756, 80.234957, 80.257616 };
string[] city_names = { "Thirunindravur", "Thiruverkadu", "Senkadu", "Milapore", "VGP Golden", "Medavakkam", "Palavakkam", "Vandalur", "Selaiyur", "Kelkattalai", "Mangadu", "TNagar", "Adyar" };
double[] latitudeandLongitude;
var sCoordlatitudeandLongitude = new List <string>();
var finallatitudeandLongitude = new List <string>();
distanceArray = new double[geographicVM.Latitude.Length, geographicVM.Longitude.Length];
var k = 0;
for (int i = 0; i < geographicVM.Latitude.Length; i++)
{
for (int j = 0; j < geographicVM.Longitude.Length; j++)
{
var sCoord = new GeoCoordinate(geographicVM.Latitude[i], geographicVM.Longitude[i]);
var eCoord = new GeoCoordinate(geographicVM.Latitude[j], geographicVM.Longitude[j]);
if (i == j)
{
if (i % 2 == 0)
{
sCoordlatitudeandLongitude.Add(sCoord.ToString() + ",D" + "," + k++);
}
else
{
sCoordlatitudeandLongitude.Add(sCoord.ToString() + ",P" + "," + k);
}
}
var text = sCoord.GetDistanceTo(eCoord) / 1609.344;
distanceArray[i, j] = Math.Round(text);
}
}
double[,] costs = distanceArray;
int num_locations = city_names.Length;
RoutingModel routingModel = new RoutingModel(geographicVM.Latitude.Length, 1, 0);
Solver solver = routingModel.solver();
string rank_name = "rank";
routingModel.AddConstantDimension(1, geographicVM.Latitude.Length, true, rank_name);
var rank_dimension = routingModel.GetDimensionOrDie(rank_name);
//Constraint MinneapolisBeforeNewYork = solver.MakeLess(routingModel.CumulVar(highPriorityVarIndex, rank_name), routingModel.CumulVar(lowPriorityVarIndex, rank_name));
/* Later needs to be worked on the Constraint for the Multiple Pickups before Delivery */
//Constraint test = routingModel.CumulVar(3, rank_name) < routingModel.CumulVar(13, rank_name);
//solver.Add(test);
RoutingSearchParameters search_parameters = RoutingModel.DefaultSearchParameters();
search_parameters.FirstSolutionStrategy =
FirstSolutionStrategy.Types.Value.LocalCheapestArc;
NodeEvaluator2 cost_between_nodes = new Cost(costs);
routingModel.SetArcCostEvaluatorOfAllVehicles(cost_between_nodes); //oder SetVehicleCost wenn Fahrzeuge unterschiedliche Kostenmatrix haben
StringBuilder route = new StringBuilder();
Assignment assignment = routingModel.SolveWithParameters(search_parameters);
if (assignment != null)
{
Console.WriteLine("Total distance: " + assignment.ObjectiveValue().ToString() + "miles");
long index = routingModel.Start(0); //vehicle 0
route.Append("Route: ");
do
{
//route.Append(city_names[routingModel.IndexToNode(index)] + " -> ");
finallatitudeandLongitude.Add(sCoordlatitudeandLongitude[routingModel.IndexToNode(index)]);
index = assignment.Value(routingModel.NextVar(index));
}while (!routingModel.IsEnd(index));
// route.Append(city_names[routingModel.IndexToNode(index)]);
finallatitudeandLongitude.Add(sCoordlatitudeandLongitude[routingModel.IndexToNode(index)]);
}
return(finallatitudeandLongitude);
}
public FeatureCollection Solve(FeatureCollection input)
{
if (!input.Features.TrueForAll(x => x.Geometry is Point))
{
throw new ArgumentException("All Feature Geometries must be of type Point");
}
int numberOfNodes = input.Features.Count;
var starts = new List <int>();
var ends = new List <int>();
int numberOfDrivers = 0;
List <long> capacities = new List <long>();
foreach (var driverNode in input.Features.Where(x => x.Properties.ContainsKey("driverId")))
{
numberOfDrivers += 1;
capacities.Add(3);
starts.Add(input.Features.IndexOf(driverNode));
ends.Add(input.Features.IndexOf(driverNode));
}
var routing = new RoutingModel(numberOfNodes, numberOfDrivers, starts.ToArray(), ends.ToArray());
AddPickupAndDropoff(input, routing);
var evaluator = SetCost(input, routing);
//SetCapacity(input, routing, capacities.ToArray());
AddTimeDimension(input, routing, evaluator);
var parameters = RoutingModel.DefaultSearchParameters();
parameters.FirstSolutionStrategy = FirstSolutionStrategy.Types.Value.PathCheapestArc;
// The problem is solved here
var solution = routing.SolveWithParameters(parameters);
var output = new FeatureCollection(input.Features);
for (int routeNumber = 0; routeNumber < numberOfDrivers; routeNumber++)
{
var positions = new List <IPosition>();
string strokeColor = "";
for (long node = routing.Start(routeNumber); !routing.IsEnd(node); node = solution.Value(routing.NextVar(node)))
{
var feature = input.Features[(int)node];
var point = (Point)feature.Geometry;
positions.Add(point.Coordinates);
if (feature.Properties.ContainsKey("marker-color"))
{
strokeColor = (string)feature.Properties["marker-color"];
}
}
if (positions.Count >= 2)
{
var properties = new Dictionary <string, object>
{
["stroke"] = strokeColor
};
output.Features.Add(new Feature(new LineString(positions), properties));
}
}
return(output);
}
// <summary>
// Получаем предложение по оптимальному расположению адресов в указанном маршруте.
// Рачет идет с учетом окон доставки. Но естественно без любых ограничений по весу и прочему.
// </summary>
// <returns>Предолженый маршрут</returns>
// <param name="route">Первоначальный маршрутный лист, чтобы взять адреса.</param>
public ProposedRoute RebuidOneRoute(RouteList route)
{
var trip = new PossibleTrip(route);
logger.Info("Подготавливаем заказы...");
PerformanceHelper.StartMeasurement($"Строим маршрут");
List <CalculatedOrder> calculatedOrders = new List <CalculatedOrder>();
foreach (var address in route.Addresses)
{
if (address.Order.DeliveryPoint.Longitude == null || address.Order.DeliveryPoint.Latitude == null)
{
continue;
}
calculatedOrders.Add(new CalculatedOrder(address.Order, null));
}
Nodes = calculatedOrders.ToArray();
distanceCalculator = new ExtDistanceCalculator(DistanceProvider.Osrm, Nodes.Select(x => x.Order.DeliveryPoint).ToArray(), StatisticsTxtAction);
PerformanceHelper.AddTimePoint(logger, $"Подготовка заказов");
logger.Info("Создаем модель...");
RoutingModel routing = new RoutingModel(Nodes.Length + 1, 1, 0);
int horizon = 24 * 3600;
routing.AddDimension(new CallbackTime(Nodes, trip, distanceCalculator), 3 * 3600, horizon, false, "Time");
var time_dimension = routing.GetDimensionOrDie("Time");
var cumulTimeOnEnd = routing.CumulVar(routing.End(0), "Time");
var cumulTimeOnBegin = routing.CumulVar(routing.Start(0), "Time");
if (route.Shift != null)
{
var shift = route.Shift;
cumulTimeOnEnd.SetMax((long)shift.EndTime.TotalSeconds);
cumulTimeOnBegin.SetMin((long)shift.StartTime.TotalSeconds);
}
routing.SetArcCostEvaluatorOfVehicle(new CallbackDistance(Nodes, distanceCalculator), 0);
for (int ix = 0; ix < Nodes.Length; ix++)
{
var startWindow = Nodes[ix].Order.DeliverySchedule.From.TotalSeconds;
var endWindow = Nodes[ix].Order.DeliverySchedule.To.TotalSeconds - trip.Driver.TimeCorrection(Nodes[ix].Order.CalculateTimeOnPoint(route.Forwarder != null));
if (endWindow < startWindow)
{
logger.Warn("Время разгрузки на точке, не помещается в диапазон времени доставки. {0}-{1}", Nodes[ix].Order.DeliverySchedule.From, Nodes[ix].Order.DeliverySchedule.To);
endWindow = startWindow;
}
time_dimension.CumulVar(ix + 1).SetRange((long)startWindow, (long)endWindow);
routing.AddDisjunction(new int[] { ix + 1 }, MaxDistanceAddressPenalty);
}
RoutingSearchParameters search_parameters = RoutingModel.DefaultSearchParameters();
search_parameters.FirstSolutionStrategy = FirstSolutionStrategy.Types.Value.ParallelCheapestInsertion;
search_parameters.TimeLimitMs = MaxTimeSeconds * 1000;
//search_parameters.FingerprintArcCostEvaluators = true;
//search_parameters.OptimizationStep = 100;
var solver = routing.solver();
PerformanceHelper.AddTimePoint(logger, $"Настроили оптимизацию");
logger.Info("Закрываем модель...");
logger.Info("Рассчет расстояний между точками...");
routing.CloseModelWithParameters(search_parameters);
distanceCalculator.FlushCache();
var lastSolution = solver.MakeLastSolutionCollector();
lastSolution.AddObjective(routing.CostVar());
routing.AddSearchMonitor(lastSolution);
routing.AddSearchMonitor(new CallbackMonitor(solver, StatisticsTxtAction, lastSolution));
PerformanceHelper.AddTimePoint(logger, $"Закрыли модель");
logger.Info("Поиск решения...");
Assignment solution = routing.SolveWithParameters(search_parameters);
PerformanceHelper.AddTimePoint(logger, $"Получили решение.");
logger.Info("Готово. Заполняем.");
Console.WriteLine("Status = {0}", routing.Status());
ProposedRoute proposedRoute = null;
if (solution != null)
{
// Solution cost.
Console.WriteLine("Cost = {0}", solution.ObjectiveValue());
time_dimension = routing.GetDimensionOrDie("Time");
int route_number = 0;
proposedRoute = new ProposedRoute(null);
long first_node = routing.Start(route_number);
long second_node = solution.Value(routing.NextVar(first_node)); // Пропускаем первый узел, так как это наша база.
proposedRoute.RouteCost = routing.GetCost(first_node, second_node, route_number);
while (!routing.IsEnd(second_node))
{
var time_var = time_dimension.CumulVar(second_node);
var rPoint = new ProposedRoutePoint(
TimeSpan.FromSeconds(solution.Min(time_var)),
TimeSpan.FromSeconds(solution.Max(time_var)),
Nodes[second_node - 1].Order
);
rPoint.DebugMaxMin = string.Format("\n({0},{1})[{3}-{4}]-{2}",
new DateTime().AddSeconds(solution.Min(time_var)).ToShortTimeString(),
new DateTime().AddSeconds(solution.Max(time_var)).ToShortTimeString(),
second_node,
rPoint.Order.DeliverySchedule.From.ToString("hh\\:mm"),
rPoint.Order.DeliverySchedule.To.ToString("hh\\:mm")
);
proposedRoute.Orders.Add(rPoint);
first_node = second_node;
second_node = solution.Value(routing.NextVar(first_node));
proposedRoute.RouteCost += routing.GetCost(first_node, second_node, route_number);
}
}
PerformanceHelper.Main.PrintAllPoints(logger);
if (distanceCalculator.ErrorWays.Count > 0)
{
logger.Debug("Ошибок получения расстояний {0}", distanceCalculator.ErrorWays.Count);
var uniqueFrom = distanceCalculator.ErrorWays.Select(x => x.FromHash).Distinct().ToList();
var uniqueTo = distanceCalculator.ErrorWays.Select(x => x.ToHash).Distinct().ToList();
logger.Debug("Уникальных точек: отправки = {0}, прибытия = {1}", uniqueFrom.Count, uniqueTo.Count);
logger.Debug("Проблемные точки отправки:\n{0}",
string.Join("; ", distanceCalculator.ErrorWays
.GroupBy(x => x.FromHash)
.Where(x => x.Count() > (uniqueTo.Count / 2))
.Select(x => CachedDistance.GetText(x.Key)))
);
logger.Debug("Проблемные точки прибытия:\n{0}",
string.Join("; ", distanceCalculator.ErrorWays
.GroupBy(x => x.ToHash)
.Where(x => x.Count() > (uniqueFrom.Count / 2))
.Select(x => CachedDistance.GetText(x.Key)))
);
}
distanceCalculator.Dispose();
return(proposedRoute);
}
public static void Main(String[] args)
{
// Instantiate the data problem.
DataModel data = new DataModel();
// Create Routing Index Manager
RoutingIndexManager manager = new RoutingIndexManager(
data.DistanceMatrix.GetLength(0),
data.VehicleNumber,
data.Depot);
// Create Routing Model.
RoutingModel routing = new RoutingModel(manager);
// Create and register a transit callback.
int transitCallbackIndex = routing.RegisterTransitCallback(
(long fromIndex, long toIndex) =>
{
// Convert from routing variable Index to distance matrix NodeIndex.
var fromNode = manager.IndexToNode(fromIndex);
var toNode = manager.IndexToNode(toIndex);
return(data.DistanceMatrix[fromNode, toNode]);
}
);
// Define cost of each arc.
routing.SetArcCostEvaluatorOfAllVehicles(transitCallbackIndex);
// Add Distance constraint.
routing.AddDimension(
transitCallbackIndex,
0,
3000,
true, // start cumul to zero
"Distance");
RoutingDimension distanceDimension = routing.GetMutableDimension("Distance");
distanceDimension.SetGlobalSpanCostCoefficient(100);
// Define Transportation Requests.
Solver solver = routing.solver();
for (int i = 0; i < data.PickupsDeliveries.GetLength(0); i++)
{
long pickupIndex = manager.NodeToIndex(data.PickupsDeliveries[i][0]);
long deliveryIndex = manager.NodeToIndex(data.PickupsDeliveries[i][1]);
routing.AddPickupAndDelivery(pickupIndex, deliveryIndex);
solver.Add(solver.MakeEquality(
routing.VehicleVar(pickupIndex),
routing.VehicleVar(deliveryIndex)));
solver.Add(solver.MakeLessOrEqual(
distanceDimension.CumulVar(pickupIndex),
distanceDimension.CumulVar(deliveryIndex)));
}
// Setting first solution heuristic.
RoutingSearchParameters searchParameters =
operations_research_constraint_solver.DefaultRoutingSearchParameters();
searchParameters.FirstSolutionStrategy =
FirstSolutionStrategy.Types.Value.PathCheapestArc;
// Solve the problem.
Assignment solution = routing.SolveWithParameters(searchParameters);
// Print solution on console.
PrintSolution(data, routing, manager, solution);
}
private static void Test()
{
string[] city_names = { "New York", "Los Angeles", "Chicago", "Minneapolis", "Denver", "Dallas", "Seattle",
"Boston", "San Francisco", "St. Louis", "Houston", "Phoenix", "Salt Lake City" };
int tsp_size = city_names.Length;
// The number of routes, which is 1 in the TSP.
int num_routes = 1;
// The depot is the starting node of the route.
int depot = 0;
// Create routing model
if (tsp_size > 0)
{
RoutingModel routing = new RoutingModel(tsp_size, num_routes, depot);
var search_parameters = RoutingModel.DefaultSearchParameters();
// Setting first solution heuristic: the
// method for finding a first solution to the problem.
search_parameters.FirstSolutionStrategy = FirstSolutionStrategy.Types.Value.PathCheapestArc;
// Setting the cost function
// Create the distance callback, which takes two arguments (the from and to node indices)
// and returns the distance between these nodes.
// routing.SetCost(new ConstantCallback());
routing.SetArcCostEvaluatorOfAllVehicles(new DistanceCallback());
var assignment = routing.SolveWithParameters(search_parameters);
Console.WriteLine("Status = {0}", routing.Status());
if (assignment != null)
{
// Solution cost.
Console.WriteLine("Total distance: = {0}", assignment.ObjectiveValue());
// Inspect solution.
// Only one route here; otherwise iterate from 0 to routing.vehicles() - 1
int route_number = 0;
long index = routing.Start(route_number); // Index of the variable for the starting node.
string route = string.Empty;
while (!routing.IsEnd(index))
{
// Convert variable indices to node indices in the displayed route.
route += city_names[routing.IndexToNode(index)] + " -> ";
index = assignment.Value(routing.NextVar(index));
route += city_names[routing.IndexToNode(index)];
}
Console.WriteLine($"Route: {route}");
}
else
{
Console.WriteLine("No solution found.");
}
}
}
// <summary>
// Метод создаем маршруты на день основываясь на данных всесенных в поля <c>Routes</c>, <c>Orders</c>,
// <c>Drivers</c> и <c>Forwarders</c>.
// </summary>
public void CreateRoutes(TimeSpan drvStartTime, TimeSpan drvEndTime)
{
WarningMessages.Clear();
ProposedRoutes.Clear(); //Очищаем сразу, так как можем выйти из метода ранее.
logger.Info("Подготавливаем заказы...");
PerformanceHelper.StartMeasurement($"Строим оптимальные маршруты");
// Создаем список поездок всех водителей. Тут перебираем всех водителей с машинами
// и создаем поездки для них, в зависимости от выбранного режима работы.
var trips = Drivers.Where(x => x.Car != null)
.OrderBy(x => x.PriorityAtDay)
.SelectMany(drv => drv.DaySchedule != null
? drv.DaySchedule.Shifts.Where(s => s.StartTime >= drvStartTime && s.StartTime < drvEndTime)
.Select(shift => new PossibleTrip(drv, shift))
: new[] { new PossibleTrip(drv, null) }
)
.ToList();
// Стыкуем уже созданные маршрутные листы с возможными поездками, на основании водителя и смены.
// Если уже созданный маршрут не найден в поездках, то создаем поездку для него.
foreach (var existRoute in Routes)
{
var trip = trips.FirstOrDefault(x => x.Driver == existRoute.Driver && x.Shift == existRoute.Shift);
if (trip != null)
{
trip.OldRoute = existRoute;
}
else
{
trips.Add(new PossibleTrip(existRoute));
}
//Проверяем все ли заказы из МЛ присутствуют в списке заказов. Если их нет. Добавляем.
foreach (var address in existRoute.Addresses)
{
if (Orders.All(x => x.Id != address.Order.Id))
{
Orders.Add(address.Order);
}
}
}
var possibleRoutes = trips.ToArray();
if (!possibleRoutes.Any())
{
AddWarning("Для построения маршрутов, нет водителей.");
return;
}
TestCars(possibleRoutes);
var areas = UoW.GetAll <District>().Where(x => x.DistrictsSet.Status == DistrictsSetStatus.Active).ToList();
List <District> unusedDistricts = new List <District>();
List <CalculatedOrder> calculatedOrders = new List <CalculatedOrder>();
// Перебираем все заказы, исключаем те которые без координат, определяем для каждого заказа район
// на основании координат. И создавая экземпляр <c>CalculatedOrder</c>, происходит подсчет сумарной
// информации о заказе. Всего бутылей, вес и прочее.
foreach (var order in Orders)
{
if (order.DeliveryPoint.Longitude == null || order.DeliveryPoint.Latitude == null)
{
continue;
}
var point = new Point((double)order.DeliveryPoint.Latitude.Value, (double)order.DeliveryPoint.Longitude.Value);
var area = areas.Find(x => x.DistrictBorder.Contains(point));
if (area != null)
{
var oldRoute = Routes.FirstOrDefault(r => r.Addresses.Any(a => a.Order.Id == order.Id));
if (oldRoute != null)
{
calculatedOrders.Add(new CalculatedOrder(order, area, false, oldRoute));
}
else if (possibleRoutes.SelectMany(x => x.Districts).Any(x => x.District.Id == area.Id))
{
var cOrder = new CalculatedOrder(order, area);
//if(possibleRoutes.Any(r => r.GeographicGroup.Id == cOrder.ShippingBase.Id))//убрать, если в автоформировании должны учавствовать заказы из всех частей города вне зависимости от того какие части города выбраны в диалоге
calculatedOrders.Add(cOrder);
}
else if (!unusedDistricts.Contains(area))
{
unusedDistricts.Add(area);
}
}
}
Nodes = calculatedOrders.ToArray();
if (unusedDistricts.Any())
{
AddWarning("Районы без водителей: {0}", string.Join(", ", unusedDistricts.Select(x => x.DistrictName)));
}
// Создаем калькулятор расчета расстояний. Он сразу запрашивает уже имеющиеся расстояния из кеша
// и в фоновом режиме начинает считать недостающую матрицу.
distanceCalculator = new ExtDistanceCalculator(DistanceProvider.Osrm, Nodes.Select(x => x.Order.DeliveryPoint).ToArray(), StatisticsTxtAction);
logger.Info("Развозка по {0} районам.", calculatedOrders.Select(x => x.District).Distinct().Count());
PerformanceHelper.AddTimePoint(logger, $"Подготовка заказов");
// Пред запуском оптимизации мы должны создать модель и внести в нее все необходимые данные.
logger.Info("Создаем модель...");
RoutingModel routing = new RoutingModel(Nodes.Length + 1, possibleRoutes.Length, 0);
// Создаем измерение со временем на маршруте.
// <c>horizon</c> - ограничивает максимально допустимое значение диапазона, чтобы не уйти за границы суток;
// <c>maxWaitTime</c> - Максимальное время ожидания водителя. То есть водитель закончил разгрузку следующий
// адрес в маршруте у него не должен быть позже чем на 4 часа ожидания.
int horizon = 24 * 3600;
int maxWaitTime = 4 * 3600;
var timeEvaluators = possibleRoutes.Select(x => new CallbackTime(Nodes, x, distanceCalculator)).ToArray();
routing.AddDimensionWithVehicleTransits(timeEvaluators, maxWaitTime, horizon, false, "Time");
var time_dimension = routing.GetDimensionOrDie("Time");
// Ниже заполняем все измерения для учета бутылей, веса, адресов, объема.
var bottlesCapacity = possibleRoutes.Select(x => (long)x.Car.MaxBottles).ToArray();
routing.AddDimensionWithVehicleCapacity(new CallbackBottles(Nodes), 0, bottlesCapacity, true, "Bottles");
var weightCapacity = possibleRoutes.Select(x => (long)x.Car.MaxWeight).ToArray();
routing.AddDimensionWithVehicleCapacity(new CallbackWeight(Nodes), 0, weightCapacity, true, "Weight");
var volumeCapacity = possibleRoutes.Select(x => (long)(x.Car.MaxVolume * 1000)).ToArray();
routing.AddDimensionWithVehicleCapacity(new CallbackVolume(Nodes), 0, volumeCapacity, true, "Volume");
var addressCapacity = possibleRoutes.Select(x => (long)(x.Driver.MaxRouteAddresses)).ToArray();
routing.AddDimensionWithVehicleCapacity(new CallbackAddressCount(Nodes.Length), 0, addressCapacity, true, "AddressCount");
var bottlesDimension = routing.GetDimensionOrDie("Bottles");
var addressDimension = routing.GetDimensionOrDie("AddressCount");
for (int ix = 0; ix < possibleRoutes.Length; ix++)
{
// Устанавливаем функцию получения стоимости маршрута.
routing.SetArcCostEvaluatorOfVehicle(new CallbackDistanceDistrict(Nodes, possibleRoutes[ix], distanceCalculator), ix);
// Добавляем фиксированный штраф за принадлежность водителя.
if (possibleRoutes[ix].Driver.DriverType.HasValue)
{
routing.SetFixedCostOfVehicle(((int)possibleRoutes[ix].Driver.DriverType) * DriverPriorityPenalty, ix);
}
else
{
routing.SetFixedCostOfVehicle(DriverPriorityPenalty * 3, ix);
}
var cumulTimeOnEnd = routing.CumulVar(routing.End(ix), "Time");
var cumulTimeOnBegin = routing.CumulVar(routing.Start(ix), "Time");
// Устанавливаем минимальные(мягкие) границы для измерений. При значениях меньше минимальных, маршрут все таки принимается,
// но вносятся некоторые штрафные очки на последнюю точку маршрута.
//bottlesDimension.SetEndCumulVarSoftLowerBound(ix, possibleRoutes[ix].Car.MinBottles, MinBottlesInRoutePenalty);
//addressDimension.SetEndCumulVarSoftLowerBound(ix, possibleRoutes[ix].Driver.MinRouteAddresses, MinAddressesInRoutePenalty);
// Устанавливаем диапазон времени для движения по маршруту в зависимости от выбраной смены,
// день, вечер и с учетом досрочного завершения водителем работы.
if (possibleRoutes[ix].Shift != null)
{
var shift = possibleRoutes[ix].Shift;
var endTime = possibleRoutes[ix].EarlyEnd.HasValue
? Math.Min(shift.EndTime.TotalSeconds, possibleRoutes[ix].EarlyEnd.Value.TotalSeconds)
: shift.EndTime.TotalSeconds;
cumulTimeOnEnd.SetMax((long)endTime);
cumulTimeOnBegin.SetMin((long)shift.StartTime.TotalSeconds);
}
else if (possibleRoutes[ix].EarlyEnd.HasValue) //Устанавливаем время окончания рабочего дня у водителя.
{
cumulTimeOnEnd.SetMax((long)possibleRoutes[ix].EarlyEnd.Value.TotalSeconds);
}
}
for (int ix = 0; ix < Nodes.Length; ix++)
{
// Проставляем на каждый адрес окно времени приезда.
var startWindow = Nodes[ix].Order.DeliverySchedule.From.TotalSeconds;
var endWindow = Nodes[ix].Order.DeliverySchedule.To.TotalSeconds - Nodes[ix].Order.CalculateTimeOnPoint(false); //FIXME Внимание здесь задаем время без экспедитора и без учета скорости водителя. Это не правильно, но другого варианта я придумать не смог.
if (endWindow < startWindow)
{
AddWarning("Время разгрузки на {2}, не помещается в диапазон времени доставки. {0}-{1}", Nodes[ix].Order.DeliverySchedule.From, Nodes[ix].Order.DeliverySchedule.To, Nodes[ix].Order.DeliveryPoint.ShortAddress);
endWindow = startWindow;
}
time_dimension.CumulVar(ix + 1).SetRange((long)startWindow, (long)endWindow);
// Добавляем абсолютно все заказы в дизюкцию. Если бы заказы небыли вдобавлены в отдельные дизьюкции
// то при не возможность доставить хоть один заказ. Все решение бы считаль не верным. Добавление каждого заказа
// в отдельную дизьюкцию, позволяет механизму не вести какой то и заказов, и все таки формировать решение с недовезенными
// заказами. Дизьюкция работает так. Он говорит, если хотя бы один заказ в этой группе(дизьюкции) доставлен,
// то все хорошо, иначе штраф. Так как у нас в кадой дизьюкции по одному заказу. Мы получаем опциональную доставку каждого заказа.
routing.AddDisjunction(new int[] { ix + 1 }, MaxDistanceAddressPenalty);
}
logger.Debug("Nodes.Length = {0}", Nodes.Length);
logger.Debug("routing.Nodes() = {0}", routing.Nodes());
logger.Debug("GetNumberOfDisjunctions = {0}", routing.GetNumberOfDisjunctions());
RoutingSearchParameters search_parameters = RoutingModel.DefaultSearchParameters();
// Setting first solution heuristic (cheapest addition).
// Указывается стратегия первоначального заполнения. Опытным путем было вычислено, что именно при
// стратегиях вставки маршруты получаются с набором точек более близких к друг другу. То есть в большей
// степени облачком. Что воспринималось человеком как более отпимальное. В отличии от большенства других
// стратегий в которых маршруты, формируюся скорее по лентами ведущими через все обезжаемые раоны. То есть водители
// чаще имели пересечения маршутов.
search_parameters.FirstSolutionStrategy = FirstSolutionStrategy.Types.Value.ParallelCheapestInsertion;
search_parameters.TimeLimitMs = MaxTimeSeconds * 1000;
// Отключаем внутреннего кеширования расчитанных значений. Опытным путем было проверено, что включение этого значения.
// Значительно(на несколько секунд) увеличивает время закрытия модели и сокращает иногда не значительно время расчета оптимизаций.
// И в принцепе становится целесообразно только на количествах заказов 300-400. При количестве заказов менее 200
// влючение отпечатков значений. Не уменьшало, а увеличивало общее время расчета. А при большом количестве заказов
// время расчета уменьшалось не значительно.
//search_parameters.FingerprintArcCostEvaluators = false;
search_parameters.FingerprintArcCostEvaluators = true;
//search_parameters.OptimizationStep = 100;
var solver = routing.solver();
PerformanceHelper.AddTimePoint(logger, $"Настроили оптимизацию");
logger.Info("Закрываем модель...");
if (
WarningMessages.Any() && !interactiveService.Question(
string.Join("\n", WarningMessages.Select(x => "⚠ " + x)),
"При построении транспортной модели обнаружены следующие проблемы:\n{0}\nПродолжить?"
)
)
{
distanceCalculator.Canceled = true;
distanceCalculator.Dispose();
return;
}
logger.Info("Рассчет расстояний между точками...");
routing.CloseModelWithParameters(search_parameters);
#if DEBUG
PrintMatrixCount(distanceCalculator.matrixcount);
#endif
//Записывем возможно не схраненый кеш в базу.
distanceCalculator.FlushCache();
//Попытка хоть как то ослеживать что происходит в момент построения. Возможно не очень правильная.
//Пришлось создавать 2 монитора.
var lastSolution = solver.MakeLastSolutionCollector();
lastSolution.AddObjective(routing.CostVar());
routing.AddSearchMonitor(lastSolution);
routing.AddSearchMonitor(new CallbackMonitor(solver, StatisticsTxtAction, lastSolution));
PerformanceHelper.AddTimePoint(logger, $"Закрыли модель");
logger.Info("Поиск решения...");
Assignment solution = routing.SolveWithParameters(search_parameters);
PerformanceHelper.AddTimePoint(logger, $"Получили решение.");
logger.Info("Готово. Заполняем.");
#if DEBUG
PrintMatrixCount(distanceCalculator.matrixcount);
#endif
Console.WriteLine("Status = {0}", routing.Status());
if (solution != null)
{
// Solution cost.
Console.WriteLine("Cost = {0}", solution.ObjectiveValue());
time_dimension = routing.GetDimensionOrDie("Time");
//Читаем полученные маршруты.
for (int route_number = 0; route_number < routing.Vehicles(); route_number++)
{
var route = new ProposedRoute(possibleRoutes[route_number]);
long first_node = routing.Start(route_number);
long second_node = solution.Value(routing.NextVar(first_node)); // Пропускаем первый узел, так как это наша база.
route.RouteCost = routing.GetCost(first_node, second_node, route_number);
while (!routing.IsEnd(second_node))
{
var time_var = time_dimension.CumulVar(second_node);
var rPoint = new ProposedRoutePoint(
TimeSpan.FromSeconds(solution.Min(time_var)),
TimeSpan.FromSeconds(solution.Max(time_var)),
Nodes[second_node - 1].Order
);
rPoint.DebugMaxMin = string.Format("\n({0},{1})[{3}-{4}]-{2} Cost:{5}",
new DateTime().AddSeconds(solution.Min(time_var)).ToShortTimeString(),
new DateTime().AddSeconds(solution.Max(time_var)).ToShortTimeString(),
second_node,
rPoint.Order.DeliverySchedule.From.ToString("hh\\:mm"),
rPoint.Order.DeliverySchedule.To.ToString("hh\\:mm"),
routing.GetCost(first_node, second_node, route_number)
);
route.Orders.Add(rPoint);
first_node = second_node;
second_node = solution.Value(routing.NextVar(first_node));
route.RouteCost += routing.GetCost(first_node, second_node, route_number);
}
if (route.Orders.Count > 0)
{
ProposedRoutes.Add(route);
logger.Debug("Маршрут {0}: {1}",
route.Trip.Driver.ShortName,
string.Join(" -> ", route.Orders.Select(x => x.DebugMaxMin))
);
}
else
{
logger.Debug("Маршрут {0}: пустой", route.Trip.Driver.ShortName);
}
}
}
#if DEBUG
logger.Debug("SGoToBase:{0}", string.Join(", ", CallbackDistanceDistrict.SGoToBase.Select(x => $"{x.Key.Driver.ShortName}={x.Value}")));
logger.Debug("SFromExistPenality:{0}", string.Join(", ", CallbackDistanceDistrict.SFromExistPenality.Select(x => $"{x.Key.Driver.ShortName}={x.Value}")));
logger.Debug("SUnlikeDistrictPenality:{0}", string.Join(", ", CallbackDistanceDistrict.SUnlikeDistrictPenality.Select(x => $"{x.Key.Driver.ShortName}={x.Value}")));
logger.Debug("SLargusPenality:{0}", string.Join(", ", CallbackDistanceDistrict.SLargusPenality.Select(x => $"{x.Key.Driver.ShortName}={x.Value}")));
#endif
if (ProposedRoutes.Count > 0)
{
logger.Info($"Предложено {ProposedRoutes.Count} маршрутов.");
}
PerformanceHelper.Main.PrintAllPoints(logger);
if (distanceCalculator.ErrorWays.Any())
{
logger.Debug("Ошибок получения расстояний {0}", distanceCalculator.ErrorWays.Count);
var uniqueFrom = distanceCalculator.ErrorWays.Select(x => x.FromHash).Distinct().ToList();
var uniqueTo = distanceCalculator.ErrorWays.Select(x => x.ToHash).Distinct().ToList();
logger.Debug("Уникальных точек: отправки = {0}, прибытия = {1}", uniqueFrom.Count, uniqueTo.Count);
logger.Debug("Проблемные точки отправки:\n{0}",
string.Join("; ", distanceCalculator.ErrorWays
.GroupBy(x => x.FromHash)
.Where(x => x.Count() > (uniqueTo.Count / 2))
.Select(x => CachedDistance.GetText(x.Key)))
);
logger.Debug("Проблемные точки прибытия:\n{0}",
string.Join("; ", distanceCalculator.ErrorWays
.GroupBy(x => x.ToHash)
.Where(x => x.Count() > (uniqueFrom.Count / 2))
.Select(x => CachedDistance.GetText(x.Key)))
);
}
}
private static void VRP(int[,] locations, int[] demands, int num_vehicles)
{
int num_locations = locations.GetLength(0);
int depot = 0; // The depot is the start and end point of each route.
// Create routing model
if (locations.Length > 0)
{
RoutingModel routing = new RoutingModel(num_locations, num_vehicles, depot);
var search_parameters = RoutingModel.DefaultSearchParameters();
// Setting first solution heuristic: the
// method for finding a first solution to the problem.
search_parameters.FirstSolutionStrategy = FirstSolutionStrategy.Types.Value.PathCheapestArc;
var distanceCallback = new DistanceLocationsCallback(locations);
// Display(distanceCallback.matrix);
routing.SetArcCostEvaluatorOfAllVehicles(distanceCallback);
// Add a dimension for demand.
long slack_max = 0;
long vehicle_capacity = 100;
bool fix_start_cumul_to_zero = true;
string demand = "Demand";
routing.AddDimension(new DemandCallback(demands), slack_max, vehicle_capacity, fix_start_cumul_to_zero, demand);
// Solve, displays a solution if any.
var assignment = routing.SolveWithParameters(search_parameters);
Console.WriteLine("Status = {0}", routing.Status());
if (assignment != null)
{
// Solution cost.
Console.WriteLine("Total distance of all routes: {0}", assignment.ObjectiveValue());
// Inspect solution.
// Only one route here; otherwise iterate from 0 to routing.vehicles() - 1
for (int vehicle_nbr = 0; vehicle_nbr < num_vehicles; vehicle_nbr++)
{
long index = routing.Start(vehicle_nbr);
long index_next = assignment.Value(routing.NextVar(index));
string route = string.Empty;
long route_dist = 0;
long route_demand = 0;
int node_index;
int node_index_next;
while (!routing.IsEnd(index_next))
{
// Convert variable indices to node indices in the displayed route.
node_index = routing.IndexToNode(index);
node_index_next = routing.IndexToNode(index_next);
route += node_index + " -> ";
// Add the distance to the next node.
route_dist += distanceCallback.Run(node_index, node_index_next);
// # Add demand.
route_demand += demands[node_index_next];
index = index_next;
index_next = assignment.Value(routing.NextVar(index));
}
node_index = routing.IndexToNode(index);
node_index_next = routing.IndexToNode(index_next);
route += node_index + " -> " + node_index_next;
route_dist += distanceCallback.Run(node_index, node_index_next);
Console.WriteLine("Route for vehicle " + vehicle_nbr + ":\n\n" + route + "\n");
Console.WriteLine("Distance of route " + vehicle_nbr + ": " + route_dist);
Console.WriteLine("Demand met by vehicle " + vehicle_nbr + ": " + route_demand + "\n");
// Console.WriteLine($"Route: {route}");
}
}
else
{
Console.WriteLine("No solution found.");
}
}
}
/// <summary>
/// Solves the current routing problem.
/// </summary>
private void Solve(int number_of_orders, int number_of_vehicles)
{
Console.WriteLine("Creating model with " + number_of_orders +
" orders and " + number_of_vehicles + " vehicles.");
// Finalizing model
int number_of_locations = locations_.Length;
RoutingModel model =
new RoutingModel(number_of_locations, number_of_vehicles,
vehicle_starts_, vehicle_ends_);
// Setting up dimensions
const int big_number = 100000;
NodeEvaluator2 manhattan_callback = new Manhattan(locations_, 1);
model.AddDimension(
manhattan_callback, big_number, big_number, false, "time");
NodeEvaluator2 demand_callback = new Demand(order_demands_);
model.AddDimension(demand_callback, 0, vehicle_capacity_, true, "capacity");
// Setting up vehicles
NodeEvaluator2[] cost_callbacks = new NodeEvaluator2[number_of_vehicles];
for (int vehicle = 0; vehicle < number_of_vehicles; ++vehicle)
{
int cost_coefficient = vehicle_cost_coefficients_[vehicle];
NodeEvaluator2 manhattan_cost_callback =
new Manhattan(locations_, cost_coefficient);
cost_callbacks[vehicle] = manhattan_cost_callback;
model.SetVehicleCost(vehicle, manhattan_cost_callback);
model.CumulVar(model.End(vehicle), "time").SetMax(
vehicle_end_time_[vehicle]);
}
// Setting up orders
for (int order = 0; order < number_of_orders; ++order)
{
model.CumulVar(order, "time").SetRange(order_time_windows_[order].start_,
order_time_windows_[order].end_);
int[] orders = { order };
model.AddDisjunction(orders, order_penalties_[order]);
}
// Solving
RoutingSearchParameters search_parameters =
RoutingModel.DefaultSearchParameters();
search_parameters.FirstSolutionStrategy =
FirstSolutionStrategy.Types.Value.AllUnperformed;
Console.WriteLine("Search");
Assignment solution = model.SolveWithParameters(search_parameters);
//protect callbacks from the GC
GC.KeepAlive(manhattan_callback);
GC.KeepAlive(demand_callback);
for (int cost_callback_index = 0; cost_callback_index < cost_callbacks.Length; cost_callback_index++)
{
GC.KeepAlive(cost_callbacks[cost_callback_index]);
}
if (solution != null)
{
String output = "Total cost: " + solution.ObjectiveValue() + "\n";
// Dropped orders
String dropped = "";
for (int order = 0; order < number_of_orders; ++order)
{
if (solution.Value(model.NextVar(order)) == order)
{
dropped += " " + order;
}
}
if (dropped.Length > 0)
{
output += "Dropped orders:" + dropped + "\n";
}
// Routes
for (int vehicle = 0; vehicle < number_of_vehicles; ++vehicle)
{
String route = "Vehicle " + vehicle + ": ";
long order = model.Start(vehicle);
if (model.IsEnd(solution.Value(model.NextVar(order))))
{
route += "Empty";
}
else
{
for (;
!model.IsEnd(order);
order = solution.Value(model.NextVar(order)))
{
IntVar local_load = model.CumulVar(order, "capacity");
IntVar local_time = model.CumulVar(order, "time");
route += order + " Load(" + solution.Value(local_load) + ") " +
"Time(" + solution.Min(local_time) + ", " +
solution.Max(local_time) + ") -> ";
}
IntVar load = model.CumulVar(order, "capacity");
IntVar time = model.CumulVar(order, "time");
route += order + " Load(" + solution.Value(load) + ") " +
"Time(" + solution.Min(time) + ", " + solution.Max(time) + ")";
}
output += route + "\n";
}
Console.WriteLine(output);
}
}
/// <summary>
/// requires data.SantaIds
/// requires data.Visits
/// requires data.HomeIndex
/// requires data.Unavailable
/// requires data.Start
/// requires data.End
/// </summary>
public static OptimizationResult Solve(RoutingData data, long timeLimitMilliseconds, ITimeWindowStrategy strategy)
{
if (false ||
data.SantaIds == null ||
data.Visits == null ||
data.Unavailable == null ||
data.SantaStartIndex == null ||
data.SantaEndIndex == null
)
{
throw new ArgumentNullException();
}
var model = new RoutingModel(data.Visits.Length, data.SantaIds.Length, data.SantaStartIndex, data.SantaEndIndex);
// setting up dimensions
var maxTime = GetMaxTime(data);
var timeCallback = new TimeEvaluator(data);
model.AddDimension(timeCallback, 0, maxTime, false, DimensionTime);
var lengthCallback = new TimeEvaluator(data);
model.AddDimension(lengthCallback, 0, maxTime, true, DimensionLength);
// set additional cost of longest day
{
var dim = model.GetDimensionOrDie(DimensionLength);
dim.SetGlobalSpanCostCoefficient(data.Cost.CostLongestDayPerHour);
}
// dimensions for breaks
var breakCallbacks = new List <BreakEvaluator>();
var breakDimensions = new List <string>();
for (int santa = 0; santa < data.NumberOfSantas; santa++)
{
var maxBreaks = GetNumberOfBreaks(data, santa);
if (maxBreaks == 0)
{
// no breaks
continue;
}
var evaluator = new BreakEvaluator(data, santa);
var dimension = GetSantaBreakDimension(santa);
model.AddDimension(evaluator, 0, maxBreaks, true, dimension);
breakCallbacks.Add(evaluator);
breakDimensions.Add(dimension);
}
// setting up santas (=vehicles)
var costCallbacks = new NodeEvaluator2[data.NumberOfSantas];
for (int santa = 0; santa < data.NumberOfSantas; santa++)
{
// must be a new instance per santa
NodeEvaluator2 costCallback = data.Input.IsAdditionalSanta(data.SantaIds[santa])
? new CostEvaluator(data, data.Cost.CostWorkPerHour + data.Cost.CostAdditionalSantaPerHour, data.Cost.CostAdditionalSanta)
: new CostEvaluator(data, data.Cost.CostWorkPerHour, 0);
costCallbacks[santa] = costCallback;
model.SetVehicleCost(santa, costCallback);
// limit time per santa
var day = data.GetDayFromSanta(santa);
var start = GetDayStart(data, day);
var end = GetDayEnd(data, day);
model.CumulVar(model.End(santa), DimensionTime).SetRange(start, end);
model.CumulVar(model.Start(santa), DimensionTime).SetRange(start, end);
// avoid visiting breaks of other santas
var breakDimension = GetSantaBreakDimension(santa);
foreach (var dimension in breakDimensions.Except(new[] { breakDimension }))
{
model.CumulVar(model.End(santa), dimension).SetMax(0);
}
}
// setting up visits (=orders)
for (int visit = 0; visit < data.NumberOfVisits; ++visit)
{
var cumulTimeVar = model.CumulVar(visit, DimensionTime);
cumulTimeVar.SetRange(data.OverallStart, data.OverallEnd);
model.AddDisjunction(new[] { visit }, data.Cost.CostNotVisitedVisit);
// add desired / unavailable according to strategy
var timeDimension = model.GetDimensionOrDie(DimensionTime);
strategy.AddConstraints(data, model, cumulTimeVar, timeDimension, visit);
}
// Solving
var searchParameters = RoutingModel.DefaultSearchParameters();
searchParameters.FirstSolutionStrategy = FirstSolutionStrategy.Types.Value.Automatic; // maybe try AllUnperformed or PathCheapestArc
searchParameters.LocalSearchMetaheuristic = LocalSearchMetaheuristic.Types.Value.GuidedLocalSearch;
searchParameters.TimeLimitMs = timeLimitMilliseconds;
var solution = model.SolveWithParameters(searchParameters);
// protect callbacks from the GC
GC.KeepAlive(timeCallback);
GC.KeepAlive(lengthCallback);
foreach (var costCallback in costCallbacks)
{
GC.KeepAlive(costCallback);
}
foreach (var breakCallback in breakCallbacks)
{
GC.KeepAlive(breakCallback);
}
Debug.WriteLine($"obj={solution?.ObjectiveValue()}");
return(CreateResult(data, model, solution));
}