/// <summary>
/// Initializes a new instance of the class.
/// </summary>
/// <param name="randomSeed">The random seed.</param>
/// <param name="maximumIterations">The maximum number of iterations.</param>
/// <param name="maximumIterationsWithoutImprovement">The maximum number of iterations without improvement.</param>
/// <param name="maximumRunningTime">The maximum number of seconds.</param>
/// <param name="maximumPathLength">The maximum path length.</param>
/// <param name="populationSize">The population size.</param>
/// <param name="randomGenesPerChromosome">The maximum number of genes whose value can be simultaneously randomly generated.</param>
/// <param name="percentageRandom">The percentage of a population which is composed of randomly generated chromosomes.</param>
/// <param name="percentageElite">The percentage of a population which is composed of the elite chromosomes of the previous population.</param>
/// <param name="probabilityMutation">The probability of mutation for each gene of a chromosome.</param>
/// <param name="crossoverType">The crossover algorithm to be used.</param>
/// <param name="mutationType">The mutation algorithm to be used.</param>
public Parameters(int randomSeed, int maximumIterations, int maximumIterationsWithoutImprovement, int maximumRunningTime, int maximumPathLength, int populationSize, int randomGenesPerChromosome, double percentageRandom, double percentageElite, double probabilityMutation, AnalysisCrossoverType crossoverType, AnalysisMutationType mutationType)
{
// Assign the value for each parameter.
RandomSeed = randomSeed;
MaximumIterations = maximumIterations;
MaximumIterationsWithoutImprovement = maximumIterationsWithoutImprovement;
MaximumRunningTime = maximumRunningTime;
MaximumPathLength = maximumPathLength;
PopulationSize = populationSize;
RandomGenesPerChromosome = randomGenesPerChromosome;
PercentageRandom = percentageRandom;
PercentageElite = percentageElite;
ProbabilityMutation = probabilityMutation;
CrossoverType = crossoverType;
MutationType = mutationType;
}
/// <summary>
/// Initializes a new default instance of the class.
/// </summary>
public Parameters()
{
// Assign the default value for each parameter.
RandomSeed = DefaultValues.RandomSeed;
MaximumIterations = DefaultValues.MaximumIterations;
MaximumIterationsWithoutImprovement = DefaultValues.MaximumIterationsWithoutImprovement;
MaximumRunningTime = DefaultValues.MaximumRunningTime;
MaximumPathLength = DefaultValues.MaximumPathLength;
PopulationSize = DefaultValues.PopulationSize;
RandomGenesPerChromosome = DefaultValues.RandomGenesPerChromosome;
PercentageRandom = DefaultValues.PercentageRandom;
PercentageElite = DefaultValues.PercentageElite;
ProbabilityMutation = DefaultValues.ProbabilityMutation;
CrossoverType = DefaultValues.CrossoverType;
MutationType = DefaultValues.MutationType;
}
/// <summary>
/// Mutates the current chromosome based on the given mutation probability.
/// </summary>
/// <param name="nodeIndex">The dictionary containing, for each node, its index in the node list.</param>
/// <param name="targetAncestors">The list containing, for each target nodes, the nodes from which it can be reached.</param>
/// <param name="powersMatrixCA">The list containing the different powers of the matrix (CA, CA^2, CA^3, ... ).</param>
/// <param name="nodeIsPreferred">The dictionary containing, for each node, if it is in the preferred node list.</param>
/// <param name="mutationType">The mutation type for the algorithm.</param>
/// <param name="mutationProbability">The probability of mutation for any gene of the chromosome.</param>
/// <param name="random">The random seed.</param>
/// <returns>The same chromosome, with the mutation operator applied on a random number of its genes.</returns>
public Chromosome Mutate(Dictionary <string, int> nodeIndex, Dictionary <string, List <string> > targetAncestors, List <Matrix <double> > powersMatrixCA, Dictionary <string, bool> nodeIsPreferred, AnalysisMutationType mutationType, double mutationProbability, Random random)
{
// Define the number of tries in which to try and find a valid chromosome.
var tries = _tries;
// Get the genes which will suffer a mutation, together with their current value.
var genesMutateDictionary = Genes.Where(item => random.NextDouble() < mutationProbability).ToDictionary(item => item.Key, item => item.Value);
// Use the specified mutation type.
switch (mutationType)
{
// If we have a standard mutation.
case AnalysisMutationType.WeightedRandom:
// Repeat while the chromosome is not valid.
while (genesMutateDictionary.Any())
{
// Decrease the number of tries.
tries--;
// Go over all of the values in the genes to mutate.
foreach (var item in genesMutateDictionary.Keys.ToList())
{
// Define a random value based on which to select a new value for the mutated gene.
var randomValue = random.NextDouble();
// Get the number of occurences of each ancestor in the current chromosome and select a gene based on the number of occurences.
var occurences = targetAncestors[item].ToDictionary(item1 => item1, item1 => Genes.Values.Count(item2 => item2 == item1) + 1);
// Get the variables required for finding a random index based on the number of occurences.
var totalOccurences = occurences.Values.Sum();
var sum = 0.0;
var randomIndex = occurences.Values.Select(item1 => sum += item1).Select(item1 => item1 / totalOccurences).ToList().FindIndex(item1 => randomValue <= item1);
// Assign a random new value from the list.
Genes[item] = occurences.ElementAt(randomIndex).Key;
}
// Check if the chromosome is valid.
if (IsValid(nodeIndex, powersMatrixCA))
{
// Exit the loop.
break;
}
// Check if we reached the last try.
else if (tries == 0)
{
// Reset the number of tries.
tries = _tries;
// Get a random gene to remove from the list of genes to mutate.
var randomGene = genesMutateDictionary.Keys.ElementAt(random.Next(genesMutateDictionary.Count()));
// Assign to it the current value.
Genes[randomGene] = genesMutateDictionary[randomGene];
// Remove it from the list of genes to mutate.
genesMutateDictionary.Remove(randomGene);
}
}
// End the switch statement.
break;
// If we have a stadard mutation with preference.
case AnalysisMutationType.WeightedRandomPreferred:
// Repeat while the chromosome is not valid.
while (genesMutateDictionary.Any())
{
// Decrease the number of tries.
tries--;
// Go over all of the values in the genes to mutate.
foreach (var item in genesMutateDictionary.Keys.ToList())
{
// Define a random value based on which to select a new value for the mutated gene.
var randomValue = random.NextDouble();
// Get the number of occurences of each ancestor in the current chromosome and select a gene based on the number of occurences. If the ancestor is preferred, then it is twice more likely to be selected.
var occurences = targetAncestors[item].ToDictionary(item1 => item1, item1 => Genes.Values.Count(item2 => item2 == item1) + 1).ToDictionary(item1 => item1.Key, item1 => nodeIsPreferred[item1.Key] ? 2 * item1.Value : item1.Value);
// Get the variables required for finding a random index based on the number of occurences.
var totalOccurences = occurences.Values.Sum();
var sum = 0.0;
var randomIndex = occurences.Values.Select(item1 => sum += item1).Select(item1 => item1 / totalOccurences).ToList().FindIndex(item1 => randomValue <= item1);
// Assign a random new value from the list.
Genes[item] = occurences.ElementAt(randomIndex).Key;
}
// Check if the chromosome is valid.
if (IsValid(nodeIndex, powersMatrixCA))
{
// Exit the loop.
break;
}
// Check if we reached the last try.
else if (tries == 0)
{
// Reset the number of tries.
tries = _tries;
// Get a random gene to remove from the list of genes to mutate.
var randomGene = genesMutateDictionary.Keys.ElementAt(random.Next(genesMutateDictionary.Count()));
// Assign to it the current value.
Genes[randomGene] = genesMutateDictionary[randomGene];
// Remove it from the list of genes to mutate.
genesMutateDictionary.Remove(randomGene);
}
}
// End the switch statement.
break;
// If we have a default mutation.
case AnalysisMutationType.Random:
// Repeat while the chromosome is not valid.
while (genesMutateDictionary.Any())
{
// Decrease the number of tries.
tries--;
// Go over all of the values in the genes to mutate.
foreach (var item in genesMutateDictionary.Keys.ToList())
{
// Assign a random new value from the list.
Genes[item] = targetAncestors[item][random.Next(targetAncestors[item].Count())];
}
// Check if the chromosome is valid.
if (IsValid(nodeIndex, powersMatrixCA))
{
// Exit the loop.
break;
}
// Check if we reached the last try.
else if (tries == 0)
{
// Reset the number of tries.
tries = _tries;
// Get a random gene to remove from the list of genes to mutate.
var randomGene = genesMutateDictionary.Keys.ElementAt(random.Next(genesMutateDictionary.Count()));
// Assign to it the current value.
Genes[randomGene] = genesMutateDictionary[randomGene];
// Remove it from the list of genes to mutate.
genesMutateDictionary.Remove(randomGene);
}
}
// End the switch statement.
break;
// If we have a default mutation with preference.
case AnalysisMutationType.RandomPreferred:
// Repeat while the chromosome is not valid.
while (genesMutateDictionary.Any())
{
// Decrease the number of tries.
tries--;
// Go over all of the values in the genes to mutate.
foreach (var item in genesMutateDictionary.Keys.ToList())
{
// Get all of the ancestors that are preferred.
var preferredAncestors = targetAncestors[item].Where(item1 => nodeIsPreferred[item1]).ToList();
// Assign a random new value from the list. If any of them are preferred, select a preferred ancestor randomly.
Genes[item] = preferredAncestors.Any() ? preferredAncestors[random.Next(preferredAncestors.Count())] : targetAncestors[item][random.Next(targetAncestors[item].Count())];
}
// Check if the chromosome is valid.
if (IsValid(nodeIndex, powersMatrixCA))
{
// Exit the loop.
break;
}
// Check if we reached the last try.
else if (tries == 0)
{
// Reset the number of tries.
tries = _tries;
// Get a random gene to remove from the list of genes to mutate.
var randomGene = genesMutateDictionary.Keys.ElementAt(random.Next(genesMutateDictionary.Count()));
// Assign to it the current value.
Genes[randomGene] = genesMutateDictionary[randomGene];
// Remove it from the list of genes to mutate.
genesMutateDictionary.Remove(randomGene);
}
}
// End the switch statement.
break;
// If we have none of the above.
default:
// End the switch statement.
break;
}
// Return the chromosome.
return(this);
}
