void Solve(int limit)
{
// Declares the optimization model.
LSModel model = localsolver.GetModel();
trucksUsed = new LSExpression[nbTrucks];
customersSequences = new LSExpression[nbTrucks];
routeDistances = new LSExpression[nbTrucks];
// Sequence of customers visited by each truck.
for (int k = 0; k < nbTrucks; k++)
{
customersSequences[k] = model.List(nbCustomers);
}
// All customers must be visited by the trucks
model.Constraint(model.Partition(customersSequences));
// Create demands and distances as arrays to be able to access it with an "at" operator
LSExpression demandsArray = model.Array(demands);
LSExpression distanceWarehouseArray = model.Array(distanceWarehouses);
LSExpression distanceArray = model.Array(distanceMatrix);
for (int k = 0; k < nbTrucks; k++)
{
LSExpression sequence = customersSequences[k];
LSExpression c = model.Count(sequence);
// A truck is used if it visits at least one customer
trucksUsed[k] = c > 0;
// The quantity needed in each route must not exceed the truck capacity
LSExpression demandSelector = model.Function(i => demandsArray[sequence[i]]);
LSExpression routeQuantity = model.Sum(model.Range(0, c), demandSelector);
model.Constraint(routeQuantity <= truckCapacity);
// Distance travelled by truck k
LSExpression distSelector = model.Function(i => distanceArray[sequence[i - 1], sequence[i]]);
routeDistances[k] = model.Sum(model.Range(1, c), distSelector)
+ model.If(c > 0, distanceWarehouseArray[sequence[0]] + distanceWarehouseArray[sequence[c - 1]], 0);
}
nbTrucksUsed = model.Sum(trucksUsed);
totalDistance = model.Sum(routeDistances);
// Objective: minimize the number of trucks used, then minimize the distance traveled
model.Minimize(nbTrucksUsed);
model.Minimize(totalDistance);
model.Close();
// Parameterizes the solver.
LSPhase phase = localsolver.CreatePhase();
phase.SetTimeLimit(limit);
localsolver.Solve();
}
/// <summary>
/// adds a constraint that time after the day-end is considered overtime
/// </summary>
/// <param name="day"></param>
/// <param name="santa"></param>
public void AddOvertimeConstraint(int day, int santa)
{
var s = GetSantaId(day, santa);
var sequence = solverVariables.VisitSequences[s];
var c = model.Count(sequence);
model.Constraint(model.If(solverVariables.SantaUsed[s],
solverVariables.SantaVisitStartingTimes[s][c - 1] + solverVariables.VisitDurationArray[sequence[c - 1]] + solverVariables.DistanceToHomeArray[sequence[c - 1]],
0) <= solverVariables.OptimizationInput.Days[day].to + solverVariables.SantaOvertime[s]);
}