static void Algorithm(int itemsAmount, int dimensions, double maxCost, double[] restrictions, double[] costs, double[,] itemsSet)//version w/o restarts.
{
int ConfigsAmount = 10;
double mutationPercent = 0.20;//FROM 0 TO 1
GeneticalAlgorithm ga = new GeneticalAlgorithm(itemsAmount, dimensions, restrictions, costs, itemsSet, ConfigsAmount, GeneticalAlgorithm.TwoPointCrossover, GeneticalAlgorithm.SinglePointMutation, mutationPercent);
int iterationNumber = 0;
while (ga.GetAbsoluteMaximalKnapsackCost() != maxCost)
{
//var watch = new Stopwatch();
//watch.Start();
ga.MakeIteration();
iterationNumber++;
if (iterationNumber % 10000 == 0)
{
Console.WriteLine(iterationNumber + ") delta with avg is " + (maxCost - ga.GetAbsoluteAverageKnapsackCost()) + "\n delta with max is " + (maxCost - ga.GetAbsoluteMaximalKnapsackCost()));
var bestCosts = ga.GetBestConfigsCosts();
Console.WriteLine("Top 3 of the best configs pool are {0}, {1}, {2}",
(maxCost - bestCosts[0]),
(maxCost - bestCosts[1]),
(maxCost - bestCosts[2]));
}
// watch.Stop();
}
Console.WriteLine("Finished in {0}", iterationNumber);
Console.ReadKey();
}
static void Algorithm(int itemsAmount, int dimensions, double maxCost, double[] restrictions, double[] costs, double[,] itemsSet, int testNumber)
{
int ConfigsAmount = 8;
double mutationPercent = 0.75;
GeneticalAlgorithm ga = new GeneticalAlgorithm(itemsAmount, dimensions, restrictions, costs, itemsSet, ConfigsAmount, GeneticalAlgorithm.BitByBitCrossover, GeneticalAlgorithm.MutateHalf, mutationPercent);
int iterationNumber = 1;
var controlWatch = new Stopwatch();
controlWatch.Start();
while (ga.GetAbsoluteMaximalKnapsackCost() != maxCost)
{
ga.MakeIteration();
iterationNumber++;
}
controlWatch.Stop();
using (StreamWriter file1 = new StreamWriter(@"C:\Users\black_000\Documents\visual studio 2015\Projects\ConsoleKnapsack\ConsoleKnapsack\out.txt", true))
file1.WriteLine(iterationNumber + " iterations, " + controlWatch.ElapsedMilliseconds + " ms");
//averageTime[testNumber].Add(controlWatch.ElapsedMilliseconds);
//averageIterations[testNumber].Add(iterationNumber);
}
static void TestAlgorithm()//First proof of concept
{
int itemsAmount = 500, dimensions = 6;
double[] restrictions = new double[] { 100, 600, 1200, 2400, 500, 2000 }, costs = new double[itemsAmount];
for (int i = 0; i < itemsAmount; i++)
{
costs[i] = rand.NextDouble() * 30;
}
double[,] itemsSet = new double[itemsAmount, dimensions];
for (int i = 0; i < itemsAmount; i++)
{
for (int j = 0; j < dimensions; j++)
{
itemsSet[i, j] = rand.NextDouble() * 50;
}
}
int ConfigsAmount = 6;
GeneticalAlgorithm ga = new GeneticalAlgorithm(itemsAmount, dimensions, restrictions, costs, itemsSet, ConfigsAmount, GeneticalAlgorithm.FixedSinglePointCrossover, GeneticalAlgorithm.SinglePointMutation, 0.75);
int iterationNumber = 0;
while (true)
{
var watch = new Stopwatch();
watch.Start();
while (watch.ElapsedMilliseconds < 200)
{
ga.MakeIteration();
iterationNumber++;
averageValuations.Enqueue(ga.GetNormaizedAveragePoolCost());
maxValuations.Enqueue(ga.GetNormalizedMaximalKnapsackCost());
}
watch.Stop();
}
}
static List <string> algorithmWithRestart(int itemsAmount, int dimensions, double maxCost, double[] restrictions, double[] costs, double[,] itemsSet)
{
int ConfigsAmount = 10, restartTime = 2 * 100000, currentMaxValueLiveLength = 0;
double PrevCost = 0;
double mutationPercent = 0.20;//FROM 0 TO 1
GeneticalAlgorithm ga = new GeneticalAlgorithm(itemsAmount, dimensions, restrictions, costs, itemsSet, ConfigsAmount, GeneticalAlgorithm.TwoPointCrossover, GeneticalAlgorithm.SinglePointMutation, mutationPercent);
int iterationNumber = 0, endIteration = 2 * 1000000;
List <double> resetPoints = new List <double>();
var workTime = new Stopwatch();
workTime.Start();
// string logFileName = "plotwithreset.txt";
// List<string> values = new List<string>();
while (ga.GetAbsoluteMaximalCostAllTime() != maxCost && iterationNumber < endIteration)
{
var watch = new Stopwatch();
watch.Start();
ga.MakeIteration();
iterationNumber++;
double tmp = ga.GetBestConfigsCosts()[0];
// values.Add(tmp.ToString());
if (tmp != PrevCost)
{
PrevCost = tmp;
currentMaxValueLiveLength = 0;
}
else
{
currentMaxValueLiveLength++;
}
/*
* if (iterationNumber % 10000 == 0)//Отрисовка
* {
* Console.Write(iterationNumber + ") ");// delta with avg is " + (maxCost - ga.GetAbsoluteAverageKnapsackCost()) + "\n delta with max is " + (maxCost - ga.GetAbsoluteMaximalKnapsackCost()));
* var bestCosts = ga.GetBestConfigsCosts();
* Console.WriteLine("Top 3 of the best configs pool are {0}, {1}, {2}, {3}, {4}",
* (maxCost - bestCosts[0]),
* (maxCost - bestCosts[1]),
* (maxCost - bestCosts[2]),
* (maxCost - bestCosts[3]),
* (maxCost - bestCosts[4]));
* }
*/
if (currentMaxValueLiveLength == restartTime)
{
var restartPercent = 0.4;
resetPoints.Add(maxCost - ga.GetBestConfigsCosts()[0]);
ga.RestartAlgorithm(restartPercent);
PrevCost = 0;
currentMaxValueLiveLength = 0;
// Console.WriteLine("Restart");
}
watch.Stop();
}
workTime.Stop();
Console.WriteLine(workTime.Elapsed.TotalSeconds.ToString());
//Can use resetPoints for Something.
//File.WriteAllLines(logFileName, values);
if (ga.GetAbsoluteMaximalCostAllTime() == maxCost)//problem solved
{
return(transformResults(iterationNumber, workTime));
}
else
{
return(transformResults(maxCost - ga.GetAbsoluteMaximalCostAllTime(), workTime));
}
}