// Check demand attended by vehicles is correct respect the capacity - FOR DEBUG
public static void checkDemand(CluVRPInstance instance, List <int>[] clusterRouteForVehicule, int[] vehicleRemSpace)
{
// Vehicle remmaining capacity is correct respect to cluster demand
int[] clusterDemand = instance.clusters_demand;
int totalDemand = 0;
// Sum the total demand for vehicle
for (int vehicle = 0; vehicle < clusterRouteForVehicule.Length; vehicle++)
{
int totalDemandOnVehicle = 0;
for (int clusterIt = 0; clusterIt < clusterRouteForVehicule[vehicle].Count; clusterIt++)
{
int cluster = clusterRouteForVehicule[vehicle][clusterIt];
totalDemandOnVehicle += clusterDemand[cluster];
}
// Sum the total demand of all vehicles
totalDemand += totalDemandOnVehicle;
// Asserts
Debug.Assert(instance.capacity - totalDemandOnVehicle < 0);
Debug.Assert(instance.capacity - totalDemandOnVehicle != vehicleRemSpace[vehicle] || vehicleRemSpace[vehicle] < 0);
}
// Assert
Debug.Assert(totalDemand == clusterDemand.Sum());
}
/*
*
* Constructor
*
*/
public CustomerStrongGRASP(CluVRPInstance instance, CluVRPSolution solution, Parameters parameters)
{
// Set variables
this.instance = instance;
this.solution = solution;
this.parameters = parameters;
// For local search execute order
if (parameters.Customer_LS_Order.Length == 0)
{
this.localSearchsOrder = new List <LocalSearch> {
LocalSearch.TwoOpt,
LocalSearch.Relocate, LocalSearch.Exchange, LocalSearch.SwapCustomers
};
}
else
{
this.localSearchsOrder = new List <LocalSearch>();
for (int i = 0; i < parameters.Customer_LS_Order.Length; i++)
{
localSearchsOrder.Add((LocalSearch)parameters.Customer_LS_Order[i]);
}
}
// End of constructor
}
// Customer solution verification
public void verifyCustomerSolution(CluVRPInstance instance)
{
// Verify number of vehicles
int numberOfVehicles;
if (instance.instance_type != Instance.GoldenIzquierdo)
{
numberOfVehicles = instance.vehicles;
Debug.Assert(customersPaths.Length == numberOfVehicles, "The number of vehicles on the customer path is incorrect");
Debug.Assert(vehiculeRouteDistance.Length == numberOfVehicles, "The number of vehicles on the route distance is incorrect");
}
else
{
numberOfVehicles = customersPaths.Length;
}
// Verify number of clusters
int numberOfClusters = instance.clusters.Length;
int clustersCounter = 0;
for (int i = 0; i < customersPaths.Length; i++)
{
clustersCounter += customersPaths[i].Length;
}
Debug.Assert(numberOfClusters == clustersCounter - (customersPaths.Length * 2) + 1, "The number of cluster in the complete travel is incorrect");
// Verify number of customers
int numberOfCustomers = instance.dimension;
int customersCounter = 0;
for (int i = 0; i < customersPaths.Length; i++)
{
for (int j = 0; j < customersPaths[i].Length; j++)
{
customersCounter += customersPaths[i][j].Count;
}
}
Debug.Assert(numberOfCustomers == customersCounter - (numberOfVehicles * 2) + 1);
// All clusters are correct
List <int>[] vehicleRoute = clusterRouteForVehicule;
for (int vehicle = 0; vehicle < vehicleRoute.Length; vehicle++)
{
List <int> clusterList = vehicleRoute[vehicle];
for (int clusterIt = 0; clusterIt < clusterList.Count; clusterIt++)
{
int clusterNumber = clusterList[clusterIt];
List <int> cluster = customersPaths[vehicle][clusterIt].ToList <int>();
List <int> clusterInstance = instance.clusters[clusterNumber].ToList <int>();
bool containsAll = Functions.ContainsAllItems(cluster, clusterInstance);
if (vehicleRoute[vehicle].Count != 2)
{
Debug.Assert(containsAll && cluster.Count == clusterInstance.Count, "All the clusters on the travel are not correct respect to their clients");
}
}
}
// Total distance is correct
Debug.Assert(Math.Truncate(totalCustomerRouteDistance) == Math.Truncate(Functions.calculateTotalTravelDistance(customersPaths, instance.customersDistanceMatrix, instance)), "The final distance is not correct");
}
// New LS to final solutions
public static void cluVRPLocalSearchs(CluVRPSolution cluVRPSolution, CluVRPInstance instance, Parameters parameters)
{
// Perform LS at cluster level
double oldTotalDistance = cluVRPSolution.totalCustomerRouteDistance;
var totalWatch = System.Diagnostics.Stopwatch.StartNew();
swapClusters(cluVRPSolution, instance, parameters);
cluVRPSolution.cluvrp_swapClusters_time += totalWatch.ElapsedMilliseconds;
totalWatch = System.Diagnostics.Stopwatch.StartNew();
swapVehicle(cluVRPSolution, instance, parameters);
cluVRPSolution.cluvrp_swapVehicle_time += totalWatch.ElapsedMilliseconds;
// If some cluster position change make LS at customer level
if (cluVRPSolution.totalCustomerRouteDistance < oldTotalDistance)
{
// Create a local search handler for cluster-level problem
CustomerStrongLocalSearch customerLocalSearch = new CustomerStrongLocalSearch(cluVRPSolution,
instance,
parameters.Customer_LS_TwoOpt_Iterations,
parameters.Customer_LS_Relocate_Iterations,
parameters.Customer_LS_Exchange_Iterations,
parameters.Customer_LS_SwapCustomers
);
// Perform one iteration of LS at customer level
customerLocalSearch.twoOpt();
customerLocalSearch.exchange();
customerLocalSearch.relocate();
customerLocalSearch.swapCustomers();
}
// End
return;
}
// Cluster solution verification
public void verifyClusterSolution(CluVRPInstance instance)
{
// All cluster was visited
bool wasVisited = false;
for (int cluster = 0; cluster < instance.clusters.Length; cluster++)
{
for (int vehicle = 0; vehicle < clusterRouteForVehicule.Length; vehicle++)
{
if (clusterRouteForVehicule[vehicle].Contains(cluster))
{
wasVisited = true;
break;
}
}
Debug.Assert(wasVisited, "All clusters are not visited");
wasVisited = false;
}
// Number of clusters visited is correct
int totalLength = 0;
for (int vehicle = 0; vehicle < clusterRouteForVehicule.Length; vehicle++)
{
totalLength += clusterRouteForVehicule[vehicle].Count;
}
Debug.Assert(instance.clusters.Length == totalLength - (2 * clusterRouteForVehicule.Length) + 1, "Number of cluster visited is incorrect");
// Vehicle remmaining capacity is correct respect to cluster demand
int[] clusterDemand = instance.clusters_demand;
int totalDemand = 0;
// Sum the total demand for vehicle
for (int vehicle = 0; vehicle < clusterRouteForVehicule.Length; vehicle++)
{
int totalDemandOnVehicle = 0;
for (int clusterIt = 0; clusterIt < clusterRouteForVehicule[vehicle].Count; clusterIt++)
{
int cluster = clusterRouteForVehicule[vehicle][clusterIt];
totalDemandOnVehicle += clusterDemand[cluster];
}
// Sum the total demand of all vehicles
totalDemand += totalDemandOnVehicle;
Debug.Assert(instance.capacity - totalDemandOnVehicle >= 0, "The total demand is more big than the capacity of a vehicle");
}
Debug.Assert(totalDemand == clusterDemand.Sum(), "The total demand is more big than the total capacity");
// Verify if all vehicules visit at least 1 cluster
// This is necessary for GVRP and GoldelBattarra instances
if (instance.instance_type == Instance.GVRP || instance.instance_type == Instance.GoldenBattarra)
{
for (int vehicle = 0; vehicle < clusterRouteForVehicule.Length; vehicle++)
{
Debug.Assert(clusterRouteForVehicule[vehicle].Count > 2, "There are vehicles that no visit clusters");
}
}
}
/*
*
* Read every instance file of InstanceSetName file and create a instance of it
*
*/
static public CluVRPInstance[] loadGVRPSetOfInstances(string InstanceSetName)
{
// Init variables
string filePath = InstanceSetName;
CluVRPInstance[] gvrpInstances;
// Main Cycle
try
{
string[] lines = System.IO.File.ReadAllLines(filePath);
gvrpInstances = new CluVRPInstance[lines.Length];
// Get all the instances setted on the file
int i = 0;
foreach (string instanceFilePath in lines)
{
// Try to parse instance
try
{
CluVRPInstance instance;
string[] instanceFileText = System.IO.File.ReadAllLines(instanceFilePath);
if (instanceFilePath.Contains("rho"))
{
instance = parseGoldenIzquierdoInstance(instanceFilePath, instanceFileText);
}
else if (instanceFilePath.Contains("Golden"))
{
instance = parseGoldenBattarraInstance(instanceFilePath, instanceFileText);
}
else
{
instance = parseGVRPInstance(instanceFilePath, instanceFileText);
}
gvrpInstances[i] = instance;
i++;
}
catch (Exception e)
{
Logger.GetInstance().logLine(e.ToString());
}
}
}catch (Exception e)
{
Logger.GetInstance().logLine(e.ToString());
return(null);
}
// Return array of instances
return(gvrpInstances);
}
// Constructor
public CustomerStrongLocalSearch(CluVRPSolution solution,
CluVRPInstance instance,
int maxIterationsWithoutImprovementTwoOpt = 100,
int maxIterationsWithoutImprovementRelocate = 100,
int maxIterationsWithoutImprovementExchange = 100,
int maxIterationsWithoutImprovementSwapCustomers = 100)
{
this.solution = solution;
this.instance = instance;
this.maxIterationsWithoutImprovementTwoOpt = maxIterationsWithoutImprovementTwoOpt;
this.maxIterationsWithoutImprovementRelocate = maxIterationsWithoutImprovementRelocate;
this.maxIterationsWithoutImprovementExchange = maxIterationsWithoutImprovementExchange;
this.maxIterationsWithoutImprovementSwapCustomers = maxIterationsWithoutImprovementSwapCustomers;
}
// Customer solution verification
public void verifyCustomerWeakSolution(CluVRPInstance instance)
{
// Verify number of vehicles
int numberOfVehicles;
if (instance.instance_type != Instance.GoldenIzquierdo)
{
numberOfVehicles = instance.vehicles;
}
else
{
numberOfVehicles = customersWeakRoute.Length;
}
Debug.Assert(customersWeakRoute.Length == numberOfVehicles, "CustomerWeak - The number of vehicles is incorrect respect to customer path");
Debug.Assert(vehiculeRouteDistance.Length == numberOfVehicles, "CustomerWeak - The number of vehicles is incorrect respect to vehicles distance vector");
// Verify number of customers and all paths start and end on depot
int numberOfCustomers = instance.dimension;
int customersCounter = 0;
for (int i = 0; i < customersWeakRoute.Length; i++)
{
customersCounter += customersWeakRoute[i].Count;
Debug.Assert(customersWeakRoute[i][0] == 1 && customersWeakRoute[i][customersWeakRoute[i].Count - 1] == 1, "CustomerWeak - There is a customer path that not start or end on the depot");
}
Debug.Assert(numberOfCustomers == customersCounter - (numberOfVehicles * 2) + 1, "CustomerWeak - The number of total customers is incorrect on the travel");
// All clusters are correct
List <int>[] vehicleRoute = clusterRouteForVehicule;
for (int vehicle = 0; vehicle < vehicleRoute.Length; vehicle++)
{
List <int> clusterList = vehicleRoute[vehicle];
int allClustersSizeSum = 0;
for (int clusterIt = 0; clusterIt < clusterList.Count; clusterIt++)
{
int clusterNumber = clusterList[clusterIt];
List <int> cluster = customersWeakRoute[vehicle].ToList <int>();
List <int> clusterInstance = instance.clusters[clusterNumber].ToList <int>();
allClustersSizeSum += clusterInstance.Count;
bool containsAll = Functions.ContainsAllItems(cluster, clusterInstance);
Debug.Assert(containsAll, "CustomerWeak - All the clusters not contains the corrects customers");
}
Debug.Assert(customersWeakRoute[vehicle].Count == allClustersSizeSum, "The total sum of customers is not correct on the travel");
}
// Total distance is correct
Debug.Assert(Math.Truncate(totalCustomerRouteDistance) == Math.Truncate(Functions.calculateCustomerTotalTravelDistanceForVehicle(customersWeakRoute, instance.customersDistanceMatrix, instance)), "CustomerWeak - The final distance is not correct");
}
// Constructor
public ClusterLocalSearch(CluVRPSolution solution,
CluVRPInstance instance,
int maxIterationsWithoutImprovementTwoOpt = 100,
int maxIterationsWithoutImprovementRelocate = 100,
int maxIterationsWithoutImprovementExchange = 100,
//int maxIterationsWithoutImprovementIVRS = 100,
//int maxIterationsWithoutImprovementIVRC = 100,
int maxIterationsWithoutImprovementIV = 100,
int maxIterationsWithoutImprovementSV = 100,
int maxIterationsWithoutImprovementSC = 100
)
{
this.solution = solution;
this.instance = instance;
this.maxIterationsWithoutImprovementTwoOpt = maxIterationsWithoutImprovementTwoOpt;
this.maxIterationsWithoutImprovementRelocate = maxIterationsWithoutImprovementRelocate;
this.maxIterationsWithoutImprovementExchange = maxIterationsWithoutImprovementExchange;
//this.maxIterationsWithoutImprovementIVRS = maxIterationsWithoutImprovementIVRS;
//this.maxIterationsWithoutImprovementIVRC = maxIterationsWithoutImprovementIVRC;
this.maxIterationsWithoutImprovementIV = maxIterationsWithoutImprovementIV;
this.maxIterationsWithoutImprovementSV = maxIterationsWithoutImprovementSV;
this.maxIterationsWithoutImprovementSC = maxIterationsWithoutImprovementSC;
}
// Calculate the total customer distance of a all vehicles
public static double calculateCustomerTotalTravelDistanceForVehicle(List <int>[] travel, double[][] customersDistanceMatrix, CluVRPInstance instance)
{
// Set variables
double totalDistance = 0;
for (int vehicle = 0; vehicle < travel.Length; vehicle++)
{
if (instance.instance_type == Instance.GoldenBattarra || instance.instance_type == Instance.GVRP)
{
totalDistance += (int)calculateCustomerTravelDistance(travel[vehicle], customersDistanceMatrix);
}
if (instance.instance_type == Instance.GoldenIzquierdo)
{
totalDistance += calculateCustomerTravelDistance(travel[vehicle], customersDistanceMatrix);
}
}
// Return total distance
return(totalDistance);
}
// Calculate the total travel (visiting all the custer and customers by each vehicle)
static public double calculateTotalTravelDistance(List <int>[][] customersCircuit, double[][] customersDistanceMatrix, CluVRPInstance instance)
{
double distance = 0;
for (int vehicle = 0; vehicle < customersCircuit.Length; vehicle++)
{
if (instance.instance_type == Instance.GoldenBattarra || instance.instance_type == Instance.GVRP)
{
distance += (int)calculateTotalTravelDistance(customersCircuit, customersDistanceMatrix, vehicle);
}
if (instance.instance_type == Instance.GoldenIzquierdo)
{
distance += calculateTotalTravelDistance(customersCircuit, customersDistanceMatrix, vehicle);
}
}
return(distance);
}
// Write a python script to draw the solution
public static void solutionDrawPythonCode(CluVRPInstance instance, CluVRPSolution solution)
{
// Lines of file
List <string> lines = new List <string>();
// Add initial lines to script
lines.Add("import matplotlib.pyplot as plt");
lines.Add("plt.figure(num=None, figsize=(24, 16), dpi=120, facecolor='w', edgecolor='k')");
// For python vars
string[] abc = new string[] { "a", "b", "c", "d", "f", "g", "h", "i", "j", "k", "l", "m", "k", "r", "t", "u", "v", "w", "y", "z",
"aa", "ab", "ac", "ad", "af", "ag", "ah", "ai", "aj", "ak", "al", "am", "ak", "ar", "at", "au", "av", "aw", "ay", "az",
"ca", "cb", "cc", "cd", "cf", "cg", "ch", "ci", "cj", "ck", "cl", "cm", "ck", "cr", "ct", "cu", "cv", "cw", "cy", "cz" };
// Array of colors
string[] colors = new string[] { "aqua", "bisque", "black", "blanchedalmond", "blue", "blueviolet", "brown", "burlywood", "cadetblue", "chartreuse", "chocolate", "coral", "cornflowerblue", "cornsilk", "crimson", "cyan", "darkblue", "darkcyan", "darkgoldenrod", "darkgray", "darkgreen", "darkgrey", "darkkhaki", "darkmagenta", "darkolivegreen", "darkorange", "darkorchid", "darkred", "darksalmon", "darkseagreen", "darkslateblue", "darkslategray", "darkslategrey", "darkturquoise", "darkviolet", "deeppink", "deepskyblue", "dimgray", "dimgrey", "dodgerblue", "firebrick", "floralwhite", "forestgreen", "fuchsia", "gainsboro", "ghostwhite", "gold", "goldenrod", "gray", "green", "greenyellow", "grey", "honeydew", "hotpink", "indianred", "indigo", "ivory", "khaki", "lavender", "lavenderblush", "lawngreen", "lemonchiffon", "lightblue", "lightcoral", "lightcyan", "lightgoldenrodyellow", "lightgray", "lightgreen", "lightgrey", "lightpink", "lightsalmon", "lightseagreen", "lightskyblue", "lightslategray", "lightslategrey", "lightsteelblue", "lightyellow", "lime", "limegreen", "linen", "magenta", "maroon", "mediumaquamarine", "mediumblue", "mediumorchid", "mediumpurple", "mediumseagreen", "mediumslateblue", "mediumspringgreen", "mediumturquoise", "mediumvioletred", "midnightblue", "mintcream", "mistyrose", "moccasin", "navajowhite", "navy", "oldlace", "olive", "olivedrab", "orange", "orangered", "orchid", "palegoldenrod", "palegreen", "paleturquoise", "palevioletred", "papayawhip", "peachpuff", "peru", "pink", "plum", "powderblue", "purple", "rebeccapurple", "red", "rosybrown", "royalblue", "saddlebrown", "salmon", "sandybrown", "seagreen", "seashell", "sienna", "silver", "skyblue", "slateblue", "slategray", "slategrey", "snow", "springgreen", "steelblue", "tan", "teal", "thistle", "tomato", "turquoise", "violet", "wheat", "white", "whitesmoke", "yellow", "yellowgreen" };
string[] vehicle_colors = new string[] { "red", "green", "blue", "orange", "purple", "cyan", "magenta", "lime", "pink", "teal", "lavender", "brown", "beige", "maroon", "mint", "olive", "coral", "navy", "grey", "white", "black" };
// Variables
int colorIt = 0;
int var1 = 0;
int var2 = 1;
string outFileName = instance.file_name + ".py";
// Code for draw the customers points
// All customers of one cluster have the same color
string array1 = abc[var1] + "= [" + instance.nodes[0].x.ToString().Replace(',', '.') + "]";
string array2 = abc[var2] + "= [" + instance.nodes[0].y.ToString().Replace(',', '.') + "]";
string array3 = "plt.plot(" + abc[0] + "," + abc[1] + ",'ro', markersize= 44, color = '" + colors[0] + "')";
lines.Add(array1);
lines.Add(array2);
lines.Add(array3);
var1 = var1 + 2;
var2 = var2 + 2;
colorIt++;
for (int clusterIt = 1; clusterIt < instance.clusters.Length; clusterIt++)
{
array1 = abc[var1] + "= [";
array2 = abc[var2] + "= [";
for (int customerIt = 0; customerIt < instance.clusters[clusterIt].Length; customerIt++)
{
int customer = instance.clusters[clusterIt][customerIt] - 1;
array1 += instance.nodes[customer].x.ToString().Replace(',', '.') + ",";
array2 += instance.nodes[customer].y.ToString().Replace(',', '.') + ",";
}
StringBuilder sb = new StringBuilder(array1);
sb[sb.Length - 1] = ']';
array1 = sb.ToString();
sb = new StringBuilder(array2);
sb[sb.Length - 1] = ']';
array2 = sb.ToString();
array3 = "plt.plot(" + abc[var1] + "," + abc[var2] + ",'ro', color = '" + colors[colorIt] + "')";
// For centroides
var1 = (var1 + 2) % abc.Length;
var2 = (var1 + 2) % abc.Length;
string array4 = abc[var1] + "= [";
string array5 = abc[var2] + "= [";
array4 += instance.clustersCentroid[clusterIt].Item1.ToString().Replace(',', '.') + "]";
array5 += instance.clustersCentroid[clusterIt].Item2.ToString().Replace(',', '.') + "]";
string array6 = "plt.plot(" + abc[var1] + "," + abc[var2] + ",'ro',markersize=22, color = '" + colors[colorIt] + "')";
// Write python code for clusters and customers
lines.Add(array1);
lines.Add(array2);
lines.Add(array3);
lines.Add(array4);
lines.Add(array5);
lines.Add(array6);
// Change color and variables name for next cluster
var1 = (var1 + 2) % abc.Length;
var2 = (var2 + 2) % abc.Length;
colorIt = (colorIt + 1) % colors.Length;
}
// Draw vehicle travel
var1 = 0;
var2 = 1;
colorIt = 0;
for (int vehicle = 0; vehicle < solution.customersPaths.Length; vehicle++)
{
array1 = abc[var1] + "= [";
array2 = abc[var2] + "= [";
for (int clusterIt = 0; clusterIt < solution.customersPaths[vehicle].Length; clusterIt++)
{
for (int customerIt = 0; customerIt < solution.customersPaths[vehicle][clusterIt].Count; customerIt++)
{
int customer = solution.customersPaths[vehicle][clusterIt][customerIt] - 1;
array1 += instance.nodes[customer].x.ToString().Replace(',', '.') + ",";
array2 += instance.nodes[customer].y.ToString().Replace(',', '.') + ",";
}
}
StringBuilder sb = new StringBuilder(array1);
sb[sb.Length - 1] = ']';
array1 = sb.ToString();
sb = new StringBuilder(array2);
sb[sb.Length - 1] = ']';
array2 = sb.ToString();
array3 = "plt.plot(" + abc[var1] + "," + abc[var2] + ", color = '" + vehicle_colors[colorIt] + "')";
// Write python code for clusters and customers
lines.Add(array1);
lines.Add(array2);
lines.Add(array3);
// Change color and variables name for next cluster
var1 = (var1 + 2) % abc.Length;
var2 = (var2 + 2) % abc.Length;
colorIt = (colorIt + 1) % vehicle_colors.Length;
}
// Add final line
lines.Add("plt.savefig('" + instance.file_name + ".png')");
// Write file
try
{
System.IO.File.WriteAllLines(outFileName, lines);
}
catch (Exception e)
{
Console.WriteLine(e.ToString());
}
// Excute script
System.Diagnostics.Process.Start(PYTHON_PATH, outFileName);
}
// Constructor
public CluVRPSolution(CluVRPInstance instance)
{
totalClusterRouteDistance = double.MaxValue;
instaceType = instance.instance_type;
}
// Try to swap all the clusters (one bye one) for all vehicles (one by one)
public static void swapVehicle(CluVRPSolution solution, CluVRPInstance instance, Parameters parameters)
{
// Cluster demand
int[] clusterDemand = instance.clusters_demand;
// More than 1 vehicle is needed
if (solution.clusterRouteForVehicule.Length < 2)
{
return;
}
// Main cycle
int iterations = 0;
while (iterations < parameters.CluVRP_LS_SwapVehicle)
{
// For random order on iterations
List <int> rndPosition = new List <int>();
for (int i = 0; i < solution.clusterRouteForVehicule.Length; i++)
{
rndPosition.Add(i);
}
Functions.Shuffle <int>(new Random(), rndPosition);
// For each vehicle 1
for (int vehicleIt1 = 0; vehicleIt1 < solution.clusterRouteForVehicule.Length; vehicleIt1++)
{
// For each vehicle 2
for (int vehicleIt2 = 0; vehicleIt2 < solution.clusterRouteForVehicule.Length; vehicleIt2++)
{
// When is not the same vehicle
if (vehicleIt1 != vehicleIt2)
{
// Select vehicle index from random position
int vehicle1 = rndPosition[vehicleIt1];
int vehicle2 = rndPosition[vehicleIt2];
// For each cluster 1 on vehicle 1
for (int cluster1 = 1; cluster1 < solution.clusterRouteForVehicule[vehicle1].Count; cluster1++)
{
// For each cluster 2 on vehicle 2
for (int cluster2 = 1; cluster2 < solution.clusterRouteForVehicule[vehicle2].Count; cluster2++)
{
// Calculate the space on vehicle if make a swap
int clusterSwappedV1 = solution.clusterRouteForVehicule[vehicle1][cluster1];
int clusterSwappedV2 = solution.clusterRouteForVehicule[vehicle2][cluster2];
int newSpaceV1 = solution.vehicleRemSpace[vehicle1] + clusterDemand[clusterSwappedV1] - clusterDemand[clusterSwappedV2];
int newSpaceV2 = solution.vehicleRemSpace[vehicle2] + clusterDemand[clusterSwappedV2] - clusterDemand[clusterSwappedV1];
// If swap is possible
if (newSpaceV1 > 0 && newSpaceV2 > 0 && clusterSwappedV1 != 0 && clusterSwappedV2 != 0 && clusterSwappedV1 != clusterSwappedV2)
{
int lastClusterSwappedV1 = solution.clusterRouteForVehicule[vehicle1][cluster1 - 1];
int lastClusterSwappedV2 = solution.clusterRouteForVehicule[vehicle2][cluster2 - 1];
int nextClusterSwappedV1 = solution.clusterRouteForVehicule[vehicle1][cluster1 + 1];
int nextClusterSwappedV2 = solution.clusterRouteForVehicule[vehicle2][cluster2 + 1];
// Calculate old distances for each vehicle
double oldDistanceVehicle1 = Functions.calculateCustomerTotalTravelDistanceForVehicle(solution.customersPaths[vehicle1], instance.customersDistanceMatrix, instance);
double oldDistanceVehicle2 = Functions.calculateCustomerTotalTravelDistanceForVehicle(solution.customersPaths[vehicle2], instance.customersDistanceMatrix, instance);
// Swap clusters
List <int> cluster1Swp = solution.customersPaths[vehicle1][cluster1];
List <int> cluster2Swp = solution.customersPaths[vehicle2][cluster2];
solution.customersPaths[vehicle1][cluster1] = cluster2Swp;
solution.customersPaths[vehicle2][cluster2] = cluster1Swp;
// Calculate new distances for each vehicle
double newDistanceVehicle1 = Functions.calculateCustomerTotalTravelDistanceForVehicle(solution.customersPaths[vehicle1], instance.customersDistanceMatrix, instance);
double newDistanceVehicle2 = Functions.calculateCustomerTotalTravelDistanceForVehicle(solution.customersPaths[vehicle2], instance.customersDistanceMatrix, instance);
// Calculate new total distance
double newDistance = solution.totalClusterRouteDistance - (oldDistanceVehicle1 + oldDistanceVehicle2) + (newDistanceVehicle1 + newDistanceVehicle2);
// If new distance is short
if (newDistance + 0.0001 < solution.totalClusterRouteDistance)
{
// Update distance and space remaining
solution.totalClusterRouteDistance = newDistance;
solution.vehicleRemSpace[vehicle1] = newSpaceV1;
solution.vehicleRemSpace[vehicle2] = newSpaceV2;
solution.clusterRouteForVehicule[vehicle1][cluster1] = clusterSwappedV2;
solution.clusterRouteForVehicule[vehicle2][cluster1] = clusterSwappedV1;
// Reset iterator
if (solution.cluvrp_swapVehicle_iterations <= iterations)
{
solution.cluster_insertVehicle_iterations = iterations;
}
iterations = 0;
// DEBUG
Logger.GetInstance().logLine("DEBUG - Improve on swapVehicle");
}
// If new distance is not short
else
{
// Undo swap
solution.customersPaths[vehicle1][cluster1] = cluster1Swp;
solution.customersPaths[vehicle2][cluster2] = cluster2Swp;
// Increase iterator
iterations++;
}
}
else
{
iterations++;
}
// End if swap is possible
} // End for cluster 2
} // End for cluster 1
} // End if is not the same vehicle
} // End for vehicle 2
} // End for vehicle 1
}
//End
return;
}
// Main GRASP handle main iteration depending if use Complete version or TwoPhase
public static CluVRPSolution Grasp(CluVRPInstance instance, Parameters parameters)
{
// For best solution
CluVRPSolution bestSolution = new CluVRPSolution(instance);
// Main cycle
int iterator = 0;
while (iterator < parameters.CluVRP_GRASPIterations)
{
// New Grasp for Cluster level instance
ClusterGRASP clusterGrasp = new ClusterGRASP(instance, parameters);
// Execute Grasp procedure
var totalWatch = System.Diagnostics.Stopwatch.StartNew();
CluVRPSolution cluVRPSolution = clusterGrasp.Grasp();
cluVRPSolution.clusterLevelTime = totalWatch.ElapsedMilliseconds;
// If solutions is not available continue with next iteration
if (cluVRPSolution.clusterRouteForVehicule == null)
{
iterator++;
continue;
}
// Verify if cluster solution is correct
cluVRPSolution.verifyClusterSolution(instance);
// New Grasp for Cluster level instance
CustomerLevel customerGrasp = null;
if (parameters.CluVRP_Version == CluVRPVersion.Strong)
{
customerGrasp = new CustomerStrongGRASP(instance, cluVRPSolution, parameters);
}
else if (parameters.CluVRP_Version == CluVRPVersion.Weak)
{
customerGrasp = new CustomerWeakGRASP(instance, cluVRPSolution, parameters);
}
// Execute Grasp procedure
totalWatch = System.Diagnostics.Stopwatch.StartNew();
customerGrasp.Grasp();
cluVRPSolution.customerLevelTime = totalWatch.ElapsedMilliseconds;
//if solution is not available continue with next iteration
if (cluVRPSolution.customersPaths == null && cluVRPSolution.customersWeakRoute == null)
{
continue;
}
// Perform LS
if ((parameters.CluVRP_LS_SwapClusters > 0 || parameters.CluVRP_LS_SwapVehicle > 0) && parameters.CluVRP_Version == CluVRPVersion.Strong)
{
cluVRPLocalSearchs(cluVRPSolution, instance, parameters);
}
// Verify if customer solution is correct
if (parameters.CluVRP_Version == CluVRPVersion.Strong)
{
cluVRPSolution.verifyCustomerSolution(instance);
}
else if (parameters.CluVRP_Version == CluVRPVersion.Weak)
{
cluVRPSolution.verifyCustomerWeakSolution(instance);
}
// Update best solution
if (cluVRPSolution.totalCustomerRouteDistance < bestSolution.totalCustomerRouteDistance)
{
bestSolution = cluVRPSolution;
bestSolution.cluVRPIterations = iterator;
}
// Increase iterator
iterator++;
}
// Return best solution
return(bestSolution);
}
// Swap Cluster heuristic (diff to the cluster levels because the customers paths has been builded)
public static void swapClusters(CluVRPSolution solution, CluVRPInstance instance, Parameters parameters)
{
// Calculate old distances for each vehicle
double[] bestVehicleDistance = new double[solution.clusterRouteForVehicule.Length];
for (int vehicleIt = 0; vehicleIt < bestVehicleDistance.Length; vehicleIt++)
{
bestVehicleDistance[vehicleIt] = Functions.calculateTotalTravelDistance(solution.customersPaths, instance.customersDistanceMatrix, vehicleIt);
}
// For each vehicle
for (int vehicle = 0; vehicle < solution.customersPaths.Length; vehicle++)
{
// Main cycle
while (true)
{
// If solution improves try with new iteration
bool solutionImproves = false;
// For each cluster1
for (int clusterIt1 = 1; clusterIt1 + 1 < solution.customersPaths[vehicle].Length; clusterIt1++)
{
// For each cluster2
for (int clusterIt2 = 1; clusterIt2 + 1 < solution.customersPaths[vehicle].Length; clusterIt2++)
{
// If is not the same cluster
if (clusterIt1 != clusterIt2)
{
// Calculate last and next cluster for cluster1
List <int> cluster1Last = solution.customersPaths[vehicle][clusterIt1 - 1];
List <int> cluster1 = solution.customersPaths[vehicle][clusterIt1];
List <int> cluster1Next = solution.customersPaths[vehicle][clusterIt1 + 1];
// Calculate last and next cluster for cluster2
List <int> cluster2Last = solution.customersPaths[vehicle][clusterIt2 - 1];
List <int> cluster2 = solution.customersPaths[vehicle][clusterIt2];
List <int> cluster2Next = solution.customersPaths[vehicle][clusterIt2 + 1];
// Perform swap
solution.customersPaths[vehicle][clusterIt1] = cluster2;
solution.customersPaths[vehicle][clusterIt2] = cluster1;
Functions.Swap(solution.clusterRouteForVehicule[vehicle], clusterIt1, clusterIt2);
// Calculate new distance
double newDistance = Functions.calculateTotalTravelDistance(solution.customersPaths, instance.customersDistanceMatrix, vehicle);
// If new distance is not better
if (solution.vehiculeRouteDistance[vehicle] <= newDistance + 0.00001)
{
// Back the changes
solution.customersPaths[vehicle][clusterIt1] = cluster1;
solution.customersPaths[vehicle][clusterIt2] = cluster2;
Functions.Swap(solution.clusterRouteForVehicule[vehicle], clusterIt1, clusterIt2);
}
else
{
// If new solution is better update distance
solution.vehiculeRouteDistance[vehicle] = newDistance;
solutionImproves = true;
}
}
}
}
// If solution not improves jump to next vehicle
if (!solutionImproves)
{
break;
}
}
}
// End
return;
}
