private static List <OperatingData> GenerateInitialPopulation()
{
var randomSolution = new RandomSolution();
var localSearch = new LocalSearch();
var population = new List <OperatingData>();
for (var i = 0; i < DAL.PopulationSize; i++)
{
var solution = new OperatingData {
UnusedNodes = DAL.Instance.Nodes.CloneList()
};
localSearch.Optimize(randomSolution.FindRouteFromRandomStart(solution));
while (population.Any(solution2 => solution2.Distance == solution.Distance))
{
solution = new OperatingData {
UnusedNodes = DAL.Instance.Nodes.CloneList()
};
localSearch.Optimize(randomSolution.FindRouteFromRandomStart(solution));
}
population.Add(solution);
}
return(population);
}
//private const int NumberOfLocalSearchResults = 1000;
//private const int EvaluationTimeInMiliseconds = 83360;
//private const int NumberOfHybridGeneticAlgorithmExecutions = 10;
//private const int PopulationSize = 20;
static void Main(string[] args)
{
DAL.Instance.ReadFromFile();
var hybridAlgorithmGlobalTimer = new Stopwatch();
var localSearchTimer = new Stopwatch();
var randomSolution = new RandomSolution();
var localSearch = new LocalSearch();
var random = new Random();
var hybridStatistics = new List <List <HybridAlgorithmStatisticsData> >(DAL.NumberOfHybridGeneticAlgorithmExecutions);
//var population = new List<OperatingData>(20);
for (var i = 0; i < DAL.NumberOfHybridGeneticAlgorithmExecutions; i++)
{
Console.WriteLine("Started iteration number: " + (i + 1));
var population = GenerateInitialPopulation();
//var hybridStatisticsData = new HybridAlgorithmStatisticsData();
var iterationNumber = 0;
//var singleExecutionTime = long.MinValue;
var hybridStatisticsSingleExecutionsList = new List <HybridAlgorithmStatisticsData>();
hybridAlgorithmGlobalTimer.Restart();
//Console.WriteLine("--- Ready to start iterating ---");
//Console.ReadKey();
//while (hybridAlgorithmGlobalTimer.ElapsedMilliseconds < DAL.EvaluationTimeInMiliseconds)
while (hybridAlgorithmGlobalTimer.ElapsedMilliseconds < DAL.EvaluationTimeInMiliseconds)
{
var parent1 = population[random.Next(0, population.Count)];
var parent2 = population[random.Next(0, population.Count)];
var worstSolution = FindWorstSolution(population);
while (parent1.Equals(parent2))
{
parent2 = population[random.Next(0, population.Count)];
}
var child = Recombine(parent1, parent2);
localSearchTimer.Reset();
localSearchTimer.Start();
localSearch.Optimize(child);
localSearchTimer.Stop();
//singleExecutionTime += localSearchTimer.ElapsedMilliseconds;
if (population.Any(solution => solution.Distance == child.Distance) == false && child.Distance < worstSolution.Distance)
{
population.Remove(worstSolution);
population.Add(child);
}
hybridStatisticsSingleExecutionsList.Add(new HybridAlgorithmStatisticsData
{
Distance = FindBestDistance(population),
ExecutionTime = localSearchTimer.Elapsed.Milliseconds,
IterationNumber = ++iterationNumber
});
if (iterationNumber % 100 == 0)
{
Console.WriteLine("--- Iteration number: " + iterationNumber + " ---");
}
}
hybridStatistics.Add(hybridStatisticsSingleExecutionsList);
Console.WriteLine("\n--- BEST DISTANCE = " + FindBestDistance(population) + " ---\n");
//DAL.Instance.HybridAlgorithmStatistics[i] = Tuple.Create(i+1, long.MinValue, FindBestDistance(population));
}
hybridAlgorithmGlobalTimer.Stop();
DAL.Instance.PrepareFileToWrite();
DAL.Instance.WriteToFileForHybridAlgorithm(hybridStatistics);
DAL.Instance.CloseFileToWrite();
Console.WriteLine("Done!");
Console.ReadKey();
}
