public override void MergeSolution(byte[][] solutions)
{
State = TaskSolverState.Merging;
SolutionDescription bestSolution = SerializeToClass <SolutionDescription>(solutions[0]);
for (int i = 1; i < solutions.Length; i++)
{
SolutionDescription nextSolution = SerializeToClass <SolutionDescription>(solutions[i]);
if (bestSolution.m_result > nextSolution.m_result)
{
bestSolution = nextSolution;
}
}
Solution = SerializeFromClass <SolutionDescription>(bestSolution);
State = TaskSolverState.Idle;
SolutionsMergingFinished.Invoke(EventArgs.Empty, this);
}
public override byte[] Solve(byte[] partialData, TimeSpan timeout)
{
if (timeout != TimeSpan.Zero)
{
timer = new Timer(timeout.TotalMilliseconds);
timer.Elapsed += TimeoutOcurred;
timer.Start();
}
solution = new SolutionDescription()
{
m_result = double.MaxValue, m_permutation = new int[0][]
};
State = TaskSolverState.Solving;
var startingDivision = SerializeToClass <List <List <int> > >(partialData);
PrepareData();
N = description.clients.Count;
actualDivision = new int[N][];
for (int i = 0; i < actualDivision.Length; i++)
{
actualDivision[i] = new int[N];
}
actualCosts = new int[N];
subsetsCount = new int[N];
int nextNr = 0;
for (int i = 0; i < startingDivision.Count; i++)
{
subsetsCount[i] = startingDivision[i].Count;
for (int j = 0; j < startingDivision[i].Count; j++)
{
actualDivision[i][j] = startingDivision[i][j];
actualCosts[i] += description.clients[startingDivision[i][j]].demand;
nextNr++;
}
}
MakeAllDivisions(nextNr, startingDivision.Count);
Solution = SerializeFromClass <SolutionDescription>(solution);
// ProblemSolvingFinished.Invoke(EventArgs.Empty, this);
State = TaskSolverState.Idle;
return(Solution);
}
private void ResolveOneDivision(int[][] oneDivision, int setsNr)
{
if (State == TaskSolverState.Timeout)
{
return;
}
/*double downPredictionsSum = 0;
* double[] downPredictions = new double[setsNr];
* for (int i = 0; i < setsNr; i++)
* {
* downPredictions[i] = KruskalAlgorithm(oneDivision[i], subsetsCount[i]);
* if (downPredictions[i] == double.MaxValue) return;
* downPredictionsSum += oneSubsetMinCost;
* if (downPredictionsSum > solution.m_result) return;
* }*/
double oneDivisionMinCost = 0;
int[][] oneDivisionMinPermutations = new int[setsNr][];
for (int i = 0; i < setsNr; i++)
{
//double oneSubsetMinCost = double.MaxValue;// 2 * downPredictions[i];
double oneSubsetMinCost = /*subsetsCount[i] < 5 ?*/ AllPermuationsSimple(oneDivision[i], subsetsCount[i]);/* :*/
// AllPermutationsComplicated(oneDivision[i], subsetsCount[i], out oneSubsetMinPermutation);
if (oneSubsetMinCost == double.MaxValue)
{
return;
}
oneDivisionMinCost += oneSubsetMinCost;
oneDivisionMinPermutations[i] = oneSubsetMinPermutation;
if (oneDivisionMinCost > solution.m_result)
{
return;
}
}
if (oneDivisionMinPermutations.Length > description.vehiclesCount)
{
List <List <int> > oneDivisionMinPermutationList;
List <List <int> > oneDiv = new List <List <int> >();
for (int i = 0; i < setsNr; i++)
{
List <int> subset = new List <int>();
for (int j = 0; j < subsetsCount[i]; i++)
{
subset.Add(oneDivision[i][j]);
}
oneDiv.Add(subset);
}
double value = LittleCarProblem0(oneDiv, out oneDivisionMinPermutationList);
if (value >= solution.m_result)
{
return;
}
oneDivisionMinPermutations = new int[oneDivisionMinPermutationList.Count][];
for (int i = 0; i < oneDivisionMinPermutations.Length; i++)
{
oneDivisionMinPermutations[i] = new int[oneDivisionMinPermutationList[i].Count];
for (int j = 0; j < oneDivisionMinPermutations[i].Length; j++)
{
oneDivisionMinPermutations[i][j] = oneDivisionMinPermutationList[i][j];
}
}
}
solution = new SolutionDescription()
{
m_permutation = oneDivisionMinPermutations, m_result = oneDivisionMinCost
};
}
