public static Solution RandomFeasibleSolution(VrptwProblem problem)
{
Solution solution = new Solution(problem);
var customersToAssign = new List <Customer>(problem.Customers);
while (customersToAssign.Count != 0)
{
Route route = new Route(problem);
route.AddCustomer(problem.Depot);
while (true)
{
float totalTime = route.TotalTime();
Customer lastOneInRoute = route.Customers.Last();
var feasibleCustomers = customersToAssign.Where(
c =>
c.ReadyTime >= totalTime + problem.GetDistance(c.Id, lastOneInRoute.Id) ||
(c.ReadyTime < totalTime + problem.GetDistance(c.Id, lastOneInRoute.Id) &&
c.DueDate >= totalTime + problem.GetDistance(c.Id, lastOneInRoute.Id))).ToList();
if (feasibleCustomers.Count > 0)
{
Customer randomCustomer = feasibleCustomers.ElementAt(RandomGenerator.NextInt(feasibleCustomers.Count()));
customersToAssign.Remove(randomCustomer);
route.AddCustomer(randomCustomer);
}
else
{
route.AddCustomer(problem.Depot);
solution.Routes.Add(route);
break;
}
}
}
return(solution);
}
public JsonResult LoadProblemInstance(string instanceId)
{
string filePath = Server.MapPath("~/Data/Homberger/" + instanceId + @".txt");
VrptwProblem problem = reader.ReadFromFile(filePath);
return(new JsonResult
{
Data = problem,
JsonRequestBehavior = JsonRequestBehavior.AllowGet
});
}
public override Chromosome RandomSolution(int geneNumber, IProblem problem)
{
VrptwProblem vrptwProblem = problem as VrptwProblem;
List <int> customers = Enumerable.Range(0, geneNumber).ToList();
customers.Shuffle();
IGene[] genes = new IGene[geneNumber];
for (int i = 0; i < geneNumber; ++i)
{
genes[i] = new CustomerGene(vrptwProblem.Customers[customers[i]]);
}
Solution solution = new Solution(vrptwProblem, genes);
return(solution);
}
public void Run(ResearchParameters parameters, string inputPath, string outputPath, Action <string, float> callback, string connectionId)
{
int distanceWeight = 1;
Dictionary <string, int> customerNumbers = new Dictionary <string, int>()
{
{ "1", parameters.RoadWeight200 },
{ "2", parameters.RoadWeight200 },
//{ "4", parameters.RoadWeight400 },
//{ "6", parameters.RoadWeight600 }, { "8", parameters.RoadWeight800 },
//{ "10", parameters.RoadWeight1000 }
};
float step = 1.0f /
(CUSTOMER_TYPES.Count() * customerNumbers.Count * CUSTOMER_INSTANCES.Count() *
(parameters.CrossoverOperators.Count + parameters.MutationOperators.Count) * parameters.RandomWalkNumber);
foreach (var type in CUSTOMER_TYPES)
{
foreach (var number in customerNumbers)
{
for (int index = 0; index < CUSTOMER_INSTANCES.Count(); ++index)
{
string instanceId = type + '_' + number.Key + '_' + CUSTOMER_INSTANCES[index];
VrptwProblem problem = reader.ReadFromFile(inputPath + @"\" + instanceId + ".txt");
FitnessFunction ff = new FitnessFunction(number.Value, distanceWeight);
Landscape landscape = new Landscape(problem, factory, ff);
foreach (var op in parameters.CrossoverOperators)
{
RunSingleResearch(landscape, parameters, op, instanceId, inputPath, outputPath,
callback, connectionId, step);
}
foreach (var op in parameters.MutationOperators)
{
RunSingleResearch(landscape, parameters, op, instanceId, inputPath, outputPath,
callback, connectionId, step);
}
}
}
}
}
/// <summary>
/// Reads the VRPTW problem instance from a text file.
/// </summary>
/// <param name="filePath">The file path.</param>
/// <returns>A VRPTW problem instance.</returns>
public VrptwProblem ReadFromFile(string filePath)
{
string name;
uint vehicleNumber, vehicleCapacity;
IList <Customer> customers = new List <Customer>();
Customer depot;
using (StreamReader sr = new StreamReader(filePath))
{
name = sr.ReadLine();
sr.ReadLine(); sr.ReadLine(); sr.ReadLine();
string vehicleData = sr.ReadLine();
ReadVehicleNumberAndCapacity(vehicleData, out vehicleNumber, out vehicleCapacity);
sr.ReadLine(); sr.ReadLine(); sr.ReadLine(); sr.ReadLine();
// reading the customers data
string customerData;
MatchCollection data;
Customer customer;
Regex customerRegex = new Regex(ROW_PATTERN);
customerData = sr.ReadLine();
data = customerRegex.Matches(customerData);
depot = ReadCustomer(data);
while ((customerData = sr.ReadLine()) != null)
{
if (string.IsNullOrWhiteSpace(customerData))
{
continue;
}
data = customerRegex.Matches(customerData);
customer = ReadCustomer(data);
customers.Add(customer);
}
}
VrptwProblem problem = new VrptwProblem(name, vehicleNumber, vehicleCapacity, depot, customers);
return(problem);
}
public void SetUp()
{
reader = new VrptwProblemReader();
problem = reader.ReadFromFile(FILE_PATH);
}
public void Test1()
{
AbstractChromosomeFactory factory = new SolutionFactory();
int[] routeWeights = new int[]
{
20000, 50000, 120000, 200000, 350000
};
int distanceWeight = 1;
string[] customerTypes = new string[] { "C1", "C2", "R1", "R2", "RC1", "RC2" };
Dictionary <string, int> customerNumbers = new Dictionary <string, int>()
{
{ "2", 20000 }, { "4", 50000 }, { "6", 120000 }, { "8", 200000 }, { "10", 350000 }
};
string[] customerInstances = new string[] { "1", "2", "3", "4", "5", "6", "7", "8", "9", "10" };
CrossoverOperator[] crossoverOps = new CrossoverOperator[]
{
new OrderCrossover(), new PartiallyMatchedCrossover(), new CycleCrossover(), new UniformBasedOrderCrossover()
};
MutationOperator[] mutationOps = new MutationOperator[]
{
new SwapOperator(), new InsertionOperator(), new InversionOperator(), new DisplacementOperator()
};
int randomWalkNumber = 2000, randomWalkSteps = 5000;
string floatPattern = "0.000", separator = ",";
float epsilon = 0.05f;
foreach (var type in customerTypes)
{
foreach (var number in customerNumbers)
{
foreach (var instance in customerInstances)
{
string instanceId = type + '_' + number.Key + '_' + instance;
VrptwProblem problem = reader.ReadFromFile(FILE_PATH + @"\" + instanceId + ".txt");
FitnessFunction ff = new FitnessFunction(number.Value, distanceWeight);
Landscape landscape = new Landscape(problem, factory, ff);
foreach (var op in crossoverOps)
{
string path = RESULT_PATH + @"\" + instanceId + "_" + op.GetId() + ".csv";
if (!File.Exists(path))
{
File.Create(path).Close();
File.ReadAllText(path);
using (TextWriter tw = new StreamWriter(path))
{
tw.WriteLine("AC, IC, PIC, DBI");
for (int i = 0; i < randomWalkNumber; ++i)
{
var rwResult = landscape.RandomWalk(randomWalkSteps, op);
float ac = Autocorrelation.Run(rwResult);
float ic = InformationContent.Run(rwResult, epsilon);
float pic = PartialInformationContent.Run(rwResult, epsilon);
float dbi = DensityBasinInformation.Run(rwResult, epsilon);
string line =
ac.ToString(floatPattern) + separator +
ic.ToString(floatPattern) + separator +
pic.ToString(floatPattern) + separator +
dbi.ToString(floatPattern);
tw.WriteLine(line);
}
}
}
}
}
}
}
}
