Represents the entire population of candidate individuals ( RSGeneticAlgorithm.TRSGAIndividual ) in the current Generation, including the
FittestIndividual.
The TRSCustomGeneticAlgorithm component seeks to solve your optimization or search problems by evolving a group or population of candidate individuals through successive generations, selecting fitter (or better) child individuals for each generation, until a solution is found. After every call to Evolve , the Population property contains the next generation of individuals (the children), with the
PreviousGeneration property holding the previous generation (the parents, what was the Population before the Evolve call).
Namespace: RSGeneticAlgorithm
Delphi
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public
property Population: TRSGAPopulation read GetPopulation write SetPopulation;
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Property Value
Type: TRSGAPopulation
The following example loops through the entire population and sets their integer genes to a random number. Then, it goes back through and outputs those integer genes:
Delphi
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var
iGene, iPop, : Integer;
begin
// for every individual in the population, write random integer gene values
for iPop := 0 to RSGeneticAlgorithm1.Population.Count - 1 do
begin
// Go through the genes
for iGene := 0 to RSGeneticAlgorithm1.Genes.Count - 1 do
if RSGeneticAlgorithm1.Genes[iGene].GeneType = gtInteger then
RSGeneticAlgorithm1.Genes[iGene].SetGeneAsInteger(RSGeneticAlgorithm1.Population[iPop].Bits, Random(256));
end;
// for every individual in the population, read their integer genes
for iPop := 0 to RSGeneticAlgorithm1.Population.Count - 1 do
begin
// write out the Name for this individual
Memo1.Lines.Add('Individual #'+IntToStr(iPop)+': '+RSGeneticAlgorithm1.Population[iPop].DisplayName);
// Go through the genes
for iGene := 0 to RSGeneticAlgorithm1.Genes.Count - 1 do
if RSGeneticAlgorithm1.Genes[iGene].GeneType = gtInteger then
Memo1.Lines.Add(IntToStr(RSGeneticAlgorithm1.Genes[iGene].GeneAsInteger(RSGeneticAlgorithm1.Population[iPop].Bits)));
end;
end;
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