public OptimizedResult OptimizeRecursion()
{
//具体优化方案在此
OptimizedResult result = RecursionMethodOptimize(this._tasks);
return(result);
}
public OptimizedResult Optimize()
{
//具体优化方案在此
//至少计算windowSize*batchSize次
OptimizedResult result = HeuristicMethodOptimize1(this._tasks, batchSize: 100,
refreshSize: 10, maxIterationCount: 2000, errorRatio: 0.05, eMatrixRatio: 1, selectDiffElement: 1);
return(result);
}
/// <summary>
/// 递归的方式，O(M!)
/// </summary>
private OptimizedResult RecursionMethodOptimize(List <Task> tasks)
{
OptimizedResult result = new OptimizedResult();
result.TimeCost = Double.MaxValue;
IList <IList <IList <Task> > > taskMatrix = ParseTasks(tasks);
int[][] selectedArray = new int[taskMatrix.Count][];
for (int i = 0; i < taskMatrix.Count; i++)
{
selectedArray[i] = new int[taskMatrix[i].Count];
}
Task[] tasksArray = new Task[tasks.Count];
DoRecursionByOptimize(taskMatrix, tasksArray, 0, selectedArray, result);
return(result);
}
public static void Main(string[] args)
{
Debugger.SetDebugMode(false);
Debugger.SetWriteConsole(true);
Scheduler schedulerTest = Scheduler.DefaultTestScheduler1();
//schedulerTest.OutPutOriginalSequence();
OptimizedResult result = null;
System.Diagnostics.Stopwatch sw = new System.Diagnostics.Stopwatch();
sw.Start();
//result = schedulerTest.OptimizeRecursion();
//Console.WriteLine("Finally time cost: " + result.TimeCost);
//Console.WriteLine("Task sequence is : " + result.ToString());
////schedulerTest.OutputSequence(result.Tasks);
//sw.Stop();
//Console.WriteLine("Calculation taked " + sw.ElapsedMilliseconds);
//Console.WriteLine(".................................");
//sw.Restart();
double[] xs = new double[100];
for (int i = 0; i < 100; i++)
{
xs[i] = schedulerTest.Optimize().TimeCost;
}
double avg = xs.Average();
double s = Math.Sqrt(xs.Sum(d => Math.Pow(d - avg, 2)) / 100);
Console.WriteLine(avg + "________" + s);
result = schedulerTest.Optimize();
Console.WriteLine("Finally time cost: " + result.TimeCost);
Console.WriteLine("Task sequence is : " + result.ToString());
//schedulerTest.OutputSequence(result.Tasks);
sw.Stop();
Console.WriteLine("Calculation taked " + sw.ElapsedMilliseconds);
Console.WriteLine("Testing Schedule Algorithm...");
Console.ReadKey();
}
/// <summary>
/// 递归执行者，结果存储于入参result
/// </summary>
private void DoRecursionByOptimize(IList <IList <IList <Task> > > tasks,
Task[] tasksArray, int index,
int[][] selectedArray,
OptimizedResult result)
{
if (index == tasksArray.Length)
{
//计算
double timeCost = CalculateSequence(tasksArray.ToList());
if (result.TimeCost > timeCost)
{
result.Tasks = tasksArray.ToList();
result.TimeCost = timeCost;
result.Counter = 0;
}
else if (result.TimeCost == timeCost)
{
result.Counter++;
}
return;
}
for (int i = 0; i < selectedArray.Length; i++)
{
for (int j = 0; j < selectedArray[i].Length; j++)
{
if (selectedArray[i][j] < tasks[i][j].Count)
{
tasksArray[index] = tasks[i][j][selectedArray[i][j]];
selectedArray[i][j]++;
DoRecursionByOptimize(tasks, tasksArray, index + 1, selectedArray, result);
selectedArray[i][j]--;
tasksArray[index] = null;
}
}
}
}
/// <summary>
/// 启发式方式
/// </summary>
private OptimizedResult HeuristicMethodOptimize1(List <Task> tasks,
int batchSize, int refreshSize,
int maxIterationCount, double errorRatio,
double eMatrixRatio, double selectDiffElement)
{
OptimizedResult result = new OptimizedResult();
result.TimeCost = Double.MaxValue;
IList <IList <IList <Task> > > taskMatrix = ParseTasks(tasks);
Task[] tasksArray = new Task[tasks.Count];
Random random = new Random();
OptimizedResult[] batchResult = new OptimizedResult[(int)(batchSize * (1 - eMatrixRatio))];
OptimizedResult[] eBatchResult = new OptimizedResult[(int)(batchSize * eMatrixRatio)];
List <OptimizedResult> sortedList = new List <OptimizedResult>(batchSize);
ProbabilityMatrix dProbablityMatrix = new ProbabilityMatrix(taskMatrix, tasks.Count);
ProbabilityMatrix eProbablityMatrix = new ProbabilityMatrix(taskMatrix, tasks.Count);
String output = "{0}::当前最优:{1:0.00},平权--均值:{2:0.00}, 标准差:{3:0.00}。动态--均值:{4:0.00}, 标准差:{5:0.00}。";
Debugger debugger = new Debugger();
int batchIndex = 0;
int iteration = 0;
while (maxIterationCount != -1 && iteration < maxIterationCount)
{
//计算一个，先搞平权的batch数量
for (batchIndex = 0; batchIndex < eBatchResult.Length; batchIndex++)
{
Tuple <int, int>[] selectArray = GenerateSequence(taskMatrix, tasksArray, random, eProbablityMatrix, selectDiffElement);
double timeCost = CalculateSequence(tasksArray.ToList());
iteration++;
OptimizedResult res = new OptimizedResult();
res.TimeCost = timeCost;
res.Tasks = tasksArray.ToList();
res.Selections = selectArray;
eBatchResult[batchIndex] = res;
if (timeCost < result.TimeCost)
{
result.Counter = 0;
result.Selections = res.Selections;
result.Tasks = res.Tasks;
result.TimeCost = res.TimeCost;
}
else if (timeCost == result.TimeCost)
{
result.Counter++;
}
}
for (batchIndex = 0; batchIndex < batchResult.Length; batchIndex++)
{
Tuple <int, int>[] selectArray = GenerateSequence(taskMatrix, tasksArray, random, dProbablityMatrix, selectDiffElement);
double timeCost = CalculateSequence(tasksArray.ToList());
iteration++;
OptimizedResult res = new OptimizedResult();
res.TimeCost = timeCost;
res.Tasks = tasksArray.ToList();
res.Selections = selectArray;
batchResult[batchIndex] = res;
if (timeCost < result.TimeCost)
{
result.Counter = 0;
result.Selections = res.Selections;
result.Tasks = res.Tasks;
result.TimeCost = res.TimeCost;
}
else if (timeCost == result.TimeCost)
{
result.Counter++;
}
}
//计算并记录各项指标
double avg = batchResult.Length == 0 ? 0 : batchResult.Average(b => b.TimeCost);
double s2r = batchResult.Length == 0 ? 0 : Math.Sqrt(batchResult.Sum(b => Math.Pow(b.TimeCost - result.TimeCost, 2)) / batchResult.Length);
double eAvg = eBatchResult.Length == 0 ? 0 : eBatchResult.Average(b => b.TimeCost);
double eS2r = eBatchResult.Length == 0 ? 0 : Math.Sqrt(eBatchResult.Sum(b => Math.Pow(b.TimeCost - result.TimeCost, 2)) / eBatchResult.Length);
debugger.StringAppend(iteration).StringAppend(" ")
.StringAppend(result.TimeCost).StringAppend(" ")
.StringAppend(eAvg).StringAppend(" ")
.StringAppend(eS2r).StringAppend(" ")
.StringAppend(avg).StringAppend(" ")
.StringAppend(s2r).StringAppend(" ")
.StringAppend("\n");
Debugger.WriteLine(String.Format(output, iteration, result.TimeCost, eAvg, eS2r, avg, s2r));
sortedList.Clear();
sortedList.AddRange(eBatchResult);
sortedList.AddRange(batchResult);
sortedList.Sort(new OptimizedResultComparator());
if (eMatrixRatio < 1)
{
//更新概率矩阵
RefreshProbabilityMatrix(dProbablityMatrix, sortedList.Take(refreshSize).ToList());
}
}
debugger.WriteTofile();
return(result);
}
