static void VNS(Instance instance, Process process, Random rnd, Stopwatch clock, string choice)
{
int typeSol = 0;
List <int>[] listArray = Utility.BuildSLComplete(instance);
PathStandard incumbentSol;
PathStandard solHeuristic = Utility.NearestNeightbor(instance, rnd, listArray);
incumbentSol = (PathStandard)solHeuristic.Clone();
Utility.PrintHeuristicSolution(instance, process, incumbentSol, incumbentSol.cost, typeSol);
do
{
TwoOpt(instance, solHeuristic);
if (incumbentSol.cost > solHeuristic.cost)
{
incumbentSol = (PathStandard)solHeuristic.Clone();
Utility.PrintHeuristicSolution(instance, process, incumbentSol, incumbentSol.cost, typeSol);
Console.WriteLine("Incumbed changed");
}
else
{
Console.WriteLine("Incumbed not changed");
}
VNS(instance, solHeuristic, rnd);
} while (clock.ElapsedMilliseconds / 1000.0 < instance.TimeLimit);
Console.WriteLine("Best distance found within the timelit is: " + incumbentSol.cost);
}
public static void SwapRoute(int c, int b, PathStandard pathG)
{
int from = b;
int to = pathG.path[from];
do
{
int tmpTo = pathG.path[to];
pathG.path[to] = from;
from = to;
to = tmpTo;
} while (from != c);
}
public static void TwoOpt(Instance instance, PathStandard pathG)
{
int indexStart = 0;
int cnt = 0;
bool found = false;
do
{
found = false;
int a = indexStart;
int b = pathG.path[a];
int c = pathG.path[b];
int d = pathG.path[c];
for (int i = 0; i < instance.NNodes - 3; i++)
{
double distAC = Point.Distance(instance.Coord[a], instance.Coord[c], instance.EdgeType);
double distBD = Point.Distance(instance.Coord[b], instance.Coord[d], instance.EdgeType);
double distAD = Point.Distance(instance.Coord[a], instance.Coord[d], instance.EdgeType);
double distBC = Point.Distance(instance.Coord[b], instance.Coord[c], instance.EdgeType);
double distTotABCD = Point.Distance(instance.Coord[a], instance.Coord[b], instance.EdgeType) +
Point.Distance(instance.Coord[c], instance.Coord[d], instance.EdgeType);
if (distAC + distBD < distTotABCD)
{
Utility.SwapRoute(c, b, pathG);
pathG.path[a] = c;
pathG.path[b] = d;
pathG.cost = pathG.cost - distTotABCD + distAC + distBD;
indexStart = 0;
cnt = 0;
found = true;
break;
}
c = d;
d = pathG.path[c];
}
if (!found)
{
indexStart = b;
cnt++;
}
} while (cnt < instance.NNodes);
}
static void TabuSearch(Instance instance, Process process, Random rnd, Stopwatch clock, string choice)
{
int typeSol = 0;
List <int>[] listArray = Utility.BuildSLComplete(instance);
PathStandard incumbentSol;
PathStandard solHeuristic = Utility.NearestNeightbor(instance, rnd, listArray);
incumbentSol = (PathStandard)solHeuristic.Clone();
Utility.PrintHeuristicSolution(instance, process, incumbentSol, incumbentSol.cost, typeSol);
Tabu tabu = new Tabu("A", instance, 100);
TabuSearch(instance, process, tabu, solHeuristic, incumbentSol, clock);
solHeuristic = (PathStandard)incumbentSol.Clone();
TwoOpt(instance, solHeuristic);
Utility.PrintHeuristicSolution(instance, process, solHeuristic, incumbentSol.cost, typeSol);
Console.WriteLine("Best distance found within the timelit is: " + incumbentSol.cost);
}
public static void PrintHeuristicSolution(Instance instance, Process process, PathStandard pathG, double incumbentCost, int typeSol)
{
//Init the StreamWriter for the current solution
StreamWriter file = new StreamWriter(instance.InputFile + ".dat", false);
//Printing the optimal solution and the GNUPlot input file
for (int i = 0; i < instance.NNodes; i++)
{
/*
* Current GNUPlot format is:
*-- previus link --
*<Blank line>
* Xi Yi <index(i)>
* Xj Yj <index(i)>
*<Blank line>
*-- next link --
*/
file.WriteLine(instance.Coord[i].X + " " + instance.Coord[i].Y + " " + (i + 1));
file.WriteLine(instance.Coord[pathG.path[i]].X + " " + instance.Coord[pathG.path[i]].Y + " " + (pathG.path[i] + 1) + "\nEdges");
}
//GNUPlot input file needs to be closed
file.Close();
//Accessing GNUPlot to read the file
if (Program.VERBOSE >= -1)
{
if (pathG.cost != incumbentCost)
{
PrintGNUPlot(process, instance.InputFile, typeSol, pathG.cost, incumbentCost);
}
else
{
PrintGNUPlot(process, instance.InputFile, typeSol, pathG.cost, -1);
}
}
}
static void LocalBranching(Cplex cplex, Instance instance, Process process, Random rnd, Stopwatch clock)
{
//Define the possible value that the radius can be assume
int[] possibleRadius = { 3, 5, 7, 10 };
//We start whit a radius of 3
int currentRange = 0;
//Don't want print every candidate incumbent solution inside the lazy constraint callback
bool BlockPrint = false;
//Define the vector where is coded the incumbent solution
double[] incumbentSol = new double[(instance.NNodes - 1) * instance.NNodes / 2];
//Variable where is store the cost of the incumbent solution
double incumbentCost = double.MaxValue;
//Create the vector conten that it will contain the last best solution find befor time limit or when it can't be improved
instance.BestSol = new double[(instance.NNodes - 1) * instance.NNodes / 2];
//Build the model
INumVar[] x = Utility.BuildModel(cplex, instance, -1);
//List use in NearestNeightbor method
List <int>[] listArray = Utility.BuildSLComplete(instance);
//Create a heuristic solution
PathStandard heuristicSol = Utility.NearestNeightbor(instance, rnd, listArray);
//Apply 2-opt algotithm in order to improve the cost to the heuristicSol
TwoOpt(instance, heuristicSol);
//The heuristic solution is the incumbent, translate the encode in the format used by Cplex
for (int i = 0; i < instance.NNodes; i++)
{
int position = Utility.xPos(i, heuristicSol.path[i], instance.NNodes);
//Set to one only the edge that belong to euristic solution
incumbentSol[position] = 1;
}
//Installation of the Lazy Constraint Callback
cplex.Use(new TSPLazyConsCallback(cplex, x, instance, process, BlockPrint));
//Set the number of thread equal to the number of logical core present in the processor
cplex.SetParam(Cplex.Param.Threads, cplex.GetNumCores());
//Provide to Cplex a warm start
cplex.AddMIPStart(x, incumbentSol);
//Create a empty expression
ILinearNumExpr expr = cplex.LinearNumExpr();
//Create the firts member of the local branch constraint
for (int i = 0; i < instance.NNodes; i++)
{
expr.AddTerm(x[Utility.xPos(i, heuristicSol.path[i], instance.NNodes)], 1);
}
//Create a new local branch constraint
IAddable localBranchConstraint = cplex.Ge(expr, instance.NNodes - possibleRadius[currentRange]);
//Add the constraint
cplex.Add(localBranchConstraint);
do
{
//Solve the model
cplex.Solve();
if (incumbentCost > cplex.GetObjValue())
{
incumbentCost = cplex.ObjValue;
incumbentSol = cplex.GetValues(x);
//Eliminate the previous local branch constraint
cplex.Remove(localBranchConstraint);
//Create an empty expression
expr = cplex.LinearNumExpr();
StreamWriter file = new StreamWriter(instance.InputFile + ".dat", false);
//Print the new incombent solution
for (int i = 0; i < instance.NNodes; i++)
{
for (int j = i + 1; j < instance.NNodes; j++)
{
int position = Utility.xPos(i, j, instance.NNodes);
if (incumbentSol[position] >= 0.5)
{
file.WriteLine(instance.Coord[i].X + " " + instance.Coord[i].Y + " " + (i + 1));
file.WriteLine(instance.Coord[j].X + " " + instance.Coord[j].Y + " " + (j + 1) + "\n");
//Create the firts member of the local branch constraint
expr.AddTerm(x[position], 1);
}
}
}
Utility.PrintGNUPlot(process, instance.InputFile, 1, incumbentCost, -1);
file.Close();
//Create a local branch constraint
localBranchConstraint = cplex.Ge(expr, instance.NNodes - possibleRadius[currentRange]);
//Add the local branch constraint
cplex.Add(localBranchConstraint);
}
else
{
if (possibleRadius[currentRange] != 10)
{
//Increase the radius
currentRange++;
//Remove the previous local branch constraint
cplex.Remove(localBranchConstraint);
//Create the new local branch constraint
localBranchConstraint = cplex.Ge(expr, instance.NNodes - possibleRadius[currentRange]);
//Add the local branch constraint to the model
cplex.Add(localBranchConstraint);
}
else
{
break;
}
}
} while (clock.ElapsedMilliseconds / 1000.0 < instance.TimeLimit);
//Store in the appropriate fields inside instance the last incumbent solution find and the relative cost
instance.BestSol = incumbentSol;
instance.BestLb = incumbentCost;
}
static void HardFixing(Cplex cplex, Instance instance, Process process, Random rnd, Stopwatch clock)
{
StreamWriter file;
//Vector used to encode the path that rappresent the best integer solution note
double[] currentIncumbentSol = new double[(instance.NNodes - 1) * instance.NNodes / 2];
//Cost of the best integer solution note
double currentIncumbentCost = Double.MaxValue;
List <int>[] listArray = Utility.BuildSLComplete(instance);
//Serve per differenziarsi rispetto alla lazy "normale" in cui stampo ogni soluzione intera(anche che non è un subtour)
bool BlockPrint = false;
const int VALUECONSITENOTIMPROV = 3;
//Defined the max number of consecutive run of cplex whithout finds a improvement of the incumbent
int consecutiveiterationNotImprov = VALUECONSITENOTIMPROV;
//Defined the percentage of edge in the current solution that fixed
double percentageFixing = 0.8;
instance.BestSol = new double[(instance.NNodes - 1) * instance.NNodes / 2];
//Create the model
INumVar[] x = Utility.BuildModel(cplex, instance, -1);
//Create a heuristic solution
PathStandard heuristicSol = Utility.NearestNeightbor(instance, rnd, listArray);
//Apply 2-opt algorithm in order to improve the costo o the heiristicSol
TwoOpt(instance, heuristicSol);
//The heuristic solution is the Incumbent, translate the encode in the format used by Cplex
for (int i = 0; i < instance.NNodes; i++)
{
int position = Utility.xPos(i, heuristicSol.path[i], instance.NNodes);
//Set to one only the edge that belong to heuristic solution
currentIncumbentSol[position] = 1;
}
currentIncumbentCost = heuristicSol.cost;
//Installation of the Lazy Constraint CallBack
TSPLazyConsCallback tspLazy = new TSPLazyConsCallback(cplex, x, instance, process, BlockPrint);
cplex.Use(tspLazy);
//Provide to Cplex a warm start
cplex.AddMIPStart(x, currentIncumbentSol);
//Set the number of thread equal to the number of logical core present in the processor
cplex.SetParam(Cplex.Param.Threads, cplex.GetNumCores());
cplex.SetParam(Cplex.LongParam.IntSolLim, 2);
do
{
//Modify the Model according to the current Incumbent solution
Utility.ModifyModel(instance, x, rnd, percentageFixing, currentIncumbentSol);
//Solve the model
cplex.Solve();
if (currentIncumbentCost > cplex.GetObjValue(Cplex.IncumbentId))
{
file = new StreamWriter(instance.InputFile + ".dat", false);
currentIncumbentCost = cplex.GetObjValue(Cplex.IncumbentId);
currentIncumbentSol = cplex.GetValues(x, Cplex.IncumbentId);
//Print solution
for (int i = 0; i < instance.NNodes; i++)
{
for (int j = i + 1; j < instance.NNodes; j++)
{
int position = Utility.xPos(i, j, instance.NNodes);
if (currentIncumbentSol[position] >= 0.5)
{
file.WriteLine(instance.Coord[i].X + " " + instance.Coord[i].Y + " " + (i + 1));
file.WriteLine(instance.Coord[j].X + " " + instance.Coord[j].Y + " " + (j + 1) + "\n");
}
}
}
file.Close();
Utility.PrintGNUPlot(process, instance.InputFile, 1, currentIncumbentCost, -1);
//Restorarion the variable consecutiveIterationNotImprov to the value VALUECONSITENOTIMPROV
consecutiveiterationNotImprov = VALUECONSITENOTIMPROV;
}
else
{
//If don't have improvement decrease variable consecutiveIterationNotImprov
consecutiveiterationNotImprov--;
}
if (consecutiveiterationNotImprov == 0)
{
if (percentageFixing > 0.2)
{
percentageFixing -= 0.1;
consecutiveiterationNotImprov = VALUECONSITENOTIMPROV;
}
else
{
consecutiveiterationNotImprov = VALUECONSITENOTIMPROV;
}
}
//Restoration the lower and upper bound of all variable.
for (int i = 0; i < x.Length; i++)
{
x[i].LB = 0;
x[i].UB = 1;
}
} while (clock.ElapsedMilliseconds / 1000.0 < instance.TimeLimit);
instance.XBest = currentIncumbentCost;
instance.BestSol = currentIncumbentSol;
//Empty line
cplex.Output().WriteLine();
cplex.Output().WriteLine("x = " + instance.XBest + "\n");
if (Program.VERBOSE >= -1)
{
cplex.ExportModel(instance.InputFile + ".lp");
}
}
static void VNS(Instance instance, PathStandard currentSol, Random rnd)
{
int a, b, c, d, e, f;
a = rnd.Next(currentSol.path.Length);
b = currentSol.path[a];
do
{
c = rnd.Next(currentSol.path.Length);
d = currentSol.path[c];
} while ((a == c && b == d) || a == d || b == c);
do
{
e = rnd.Next(currentSol.path.Length);
f = currentSol.path[e];
} while ((e == a && f == b) || e == b || f == a || (e == c && f == d) || e == d || f == c);
List <int> order = new List <int>();
for (int i = 0, index = 0; i < currentSol.path.Length && order.Count != 4; i++, index = currentSol.path[index])
{
if (a == index)
{
order.Add(a);
order.Add(b);
i++;
index = currentSol.path[index];
}
else if (c == index)
{
order.Add(c);
order.Add(d);
i++;
index = currentSol.path[index];
}
else if (e == index)
{
order.Add(e);
order.Add(f);
i++;
index = currentSol.path[index];
}
}
if (order[0] != a && order[2] != a)
{
order.Add(a);
order.Add(b);
}
else if (order[0] != c && order[2] != c)
{
order.Add(c);
order.Add(d);
}
else
{
order.Add(e);
order.Add(f);
}
Utility.SwapRoute(order[2], order[1], currentSol);
currentSol.path[order[0]] = order[2];
Utility.SwapRoute(order[4], order[3], currentSol);
currentSol.path[order[1]] = order[4];
currentSol.path[order[3]] = order[5];
currentSol.cost += Point.Distance(instance.Coord[order[0]], instance.Coord[order[2]], instance.EdgeType) +
Point.Distance(instance.Coord[order[1]], instance.Coord[order[4]], instance.EdgeType) +
Point.Distance(instance.Coord[order[3]], instance.Coord[order[5]], instance.EdgeType) -
Point.Distance(instance.Coord[a], instance.Coord[b], instance.EdgeType) -
Point.Distance(instance.Coord[c], instance.Coord[d], instance.EdgeType) -
Point.Distance(instance.Coord[e], instance.Coord[f], instance.EdgeType);
}
static void TabuSearch(Instance instance, Process process, Tabu tabu, PathStandard currentSol, PathStandard incumbentPath, Stopwatch clock)
{
int typeSol;
int indexStart = 0;
string nextBestMove = "";
string nextWorstMove = "";
double bestGain = double.MaxValue;
double worstGain = double.MinValue;
int a, b, c, d;
double distAC, distBD, distTotABCD;
do
{
for (int j = 0; j < instance.NNodes; j++, indexStart = b)
{
a = indexStart;
b = currentSol.path[a];
c = currentSol.path[b];
d = currentSol.path[c];
for (int i = 0; i < instance.NNodes - 3; i++, c = d, d = currentSol.path[c])
{
if (!tabu.IsTabu(a, c) && !tabu.IsTabu(b, d))
{
distAC = Point.Distance(instance.Coord[a], instance.Coord[c], instance.EdgeType);
distBD = Point.Distance(instance.Coord[b], instance.Coord[d], instance.EdgeType);
distTotABCD = Point.Distance(instance.Coord[a], instance.Coord[b], instance.EdgeType) +
Point.Distance(instance.Coord[c], instance.Coord[d], instance.EdgeType);
if ((distAC + distBD) - distTotABCD < bestGain && (distAC + distBD) != distTotABCD)
{
nextBestMove = a + ";" + b + ";" + c + ";" + d;
bestGain = (distAC + distBD) - distTotABCD;
}
if ((distAC + distBD) - distTotABCD > worstGain && (distAC + distBD) != distTotABCD)
{
nextWorstMove = a + ";" + b + ";" + c + ";" + d;
worstGain = (distAC + distBD) - distTotABCD;
}
}
}
}
string[] currentElements = nextBestMove.Split(';');
a = int.Parse(currentElements[0]);
b = int.Parse(currentElements[1]);
c = int.Parse(currentElements[2]);
d = int.Parse(currentElements[3]);
Utility.SwapRoute(c, b, currentSol);
currentSol.path[a] = c;
currentSol.path[b] = d;
currentSol.cost += bestGain;
if (incumbentPath.cost > currentSol.cost)
{
incumbentPath = (PathGenetic)currentSol.Clone();
}
if (bestGain < 0)
{
typeSol = 0;
}
else
{
tabu.AddTabu(a, b, c, d);
typeSol = 1;
}
Utility.PrintHeuristicSolution(instance, process, currentSol, incumbentPath.cost, typeSol);
bestGain = double.MaxValue;
worstGain = double.MinValue;
} while (clock.ElapsedMilliseconds / 1000.0 < instance.TimeLimit);
}
