public static Dna Cross(Dna a, Dna b)
{
Dna res = new Dna();
Int32 aCount = a.Genom.Count;
Int32 bCount = a.Genom.Count;
res.Genom = new List <Int32>(aCount);
if (aCount <= bCount)
{
for (int i = 0; i < aCount; i++)
{
res.Genom.Add((i << 1 & 1) == 0 ? a.Genom[i] : b.Genom[i]);
}
}
else
{
Int32 point = bCount;
for (int i = 0; i < aCount; i++)
{
if (i < point)
{
res.Genom.Add((i << 1 & 1) == 0 ? a.Genom[i] : b.Genom[i]);
}
else
{
res.Genom.Add(a.Genom[i]);
}
}
}
return(res);
}
public static Dna New(Node[] nodes, Int32 start, Random rand, object randLock)
{
Dna res = new Dna();
Int32 pathLen;
lock (randLock) pathLen = rand.Next(nodes.Length - 1, nodes.Length + (nodes.Length >> 1));
Int32 nodeIndex = start;
Int32 lastNode;
res.Genom = new List <Int32>(pathLen);
for (int i = 0; i < pathLen; i++)
{
lastNode = nodeIndex;
res.Genom.Add(nodeIndex);
lock (randLock) nodeIndex = nodes[nodeIndex].NodesId[rand.Next(0, nodes[nodeIndex].NodesId.Length)];
}
return(res);
}
public bool Start(Int32 population, Int32 generations, Int32 startNode, Int32 ver)
{
Edge[] srcEdge = edges.ToArray();
Node[] srcNode = nodes.ToArray();
individuals = new List <Dna>(population);
List <Dna> nexIndividuals = new List <Dna>(population);
Int32 populationLen;
Parallel.For(0, population, x =>
{
var tmp = Dna.New(srcNode, startNode, rand, randLock);
lock (individualsLock) individuals.Add(tmp);
});
population /= 2;
for (int i = 0; i < generations; i++)
{
individuals = individuals.AsParallel().Where(x => x.Validate(srcEdge, srcNode)).OrderBy(x => x.Length(srcEdge)).ToList();
if (i % callbackStep == 0)
{
if (individuals.Count != 0)
{
UpdateGenerationStep?.Invoke(i.ToString(), individuals.First().Length(srcEdge).ToString(), individuals.AsParallel().Average(x => x.Length(srcEdge)).ToString());
}
else
{
UpdateGenerationStep?.Invoke(i.ToString(), "NaN", "NaN");
}
}
if (individuals.Count == 0)
{
individuals.Clear();
Parallel.For(0, population, x =>
{
var tmp = Dna.New(srcNode, startNode, rand, randLock);
lock (individualsLock) individuals.Add(tmp);
});
}
populationLen = individuals.Count;
nexIndividuals = new List <Dna>(individuals.Take(populationLen >> 1));
Parallel.For(0, population >> 1, x =>
{
Int32 ia, ib;
lock (randLock)
{
ia = rand.Next(0, populationLen >> 1);
ib = rand.Next(0, populationLen >> 1);
}
if (ia == ib)
{
ib = (ib + 1) % populationLen;
}
var tmp = Dna.Cross(individuals[ia], individuals[ib]);
lock (individualsLock) nexIndividuals.Add(tmp);
tmp = Dna.Cross(individuals[ib], individuals[ia]);
lock (individualsLock) nexIndividuals.Add(tmp);
tmp = Dna.New(srcNode, startNode, rand, randLock);
lock (individualsLock) nexIndividuals.Add(tmp);
tmp = Dna.New(srcNode, startNode, rand, randLock);
lock (individualsLock) nexIndividuals.Add(tmp);
});
individuals = new List <Dna>(nexIndividuals);
Parallel.For(0, individuals.Count, x => individuals[x].Mutate(ver, rand, randLock, srcNode));
}
individuals = individuals.AsParallel().Where(x => x.Validate(srcEdge, srcNode)).OrderBy(x => x.Length(srcEdge)).ToList();
if (individuals.Count == 0)
{
return(false);
}
return(true);
}
