Prepares the genetic component for evolution (or resets the genetic population to start over). On calling the Initialization method, the Population is set to the
InitialPopulation size. The
OnInitialization method is called. Then, the Population's DNA are randomized and each individual's fitness is evaluated.
Namespace: RSGeneticBase
Delphi
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public
procedure Initialize; virtual;
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The following example runs the genetic algorithm component using the different selection methods to solve the N queens problem:
Delphi
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procedure TForm1.btnRunClick(Sender: TObject);
var
SavePop: TRSGAPopulation;
Gen: Integer;
begin
Screen.Cursor := crHourGlass;
// save population as is
SavePop := TRSGAPopulation.Create(nil, RSGeneticAlgorithm1.Population.ItemClass);
try
if not RSGeneticAlgorithm1.Initialized then
RSGeneticAlgorithm1.Initialize;
SavePop.Assign(RSGeneticAlgorithm1.Population);
Gen := RSGeneticAlgorithm1.Generation;
FCurrentSeries := RouletteSeries;
RunSelectionMethod( smRoulette, Gen, SavePop );
FCurrentSeries := RandomSeries;
RunSelectionMethod( smRandom, Gen, SavePop );
FCurrentSeries := TournamentSeries;
RunSelectionMethod( smTournament, Gen, SavePop );
FCurrentSeries := StochasticTournamentSeries;
RunSelectionMethod( smStochasticTournament, Gen, SavePop );
FCurrentSeries := ElitistSeries;
RunSelectionMethod( smElitist, Gen, SavePop );
finally
Screen.Cursor := crDefault;
SavePop.Free;
end;
end;
procedure TForm1.RunSelectionMethod( SelectionMethod: TGASelectionMethod; CurrentGeneration: Integer; InitialPopulation: TRSGAPopulation );
var
i: Integer;
begin
RSGeneticAlgorithm1.SelectionMethod := SelectionMethod;
RSGeneticAlgorithm1.Generation := CurrentGeneration;
RSGeneticAlgorithm1.Population := InitialPopulation;
RSGeneticAlgorithm1.Evolve(StrToInt(Edit1.Text));
// print statistics
with RSGeneticAlgorithm1 do
begin
Memo1.Lines.Add('');
Memo1.Lines.Add('Selection Method: '+GetEnumName(TypeInfo(TGASelectionMethod), Ord(RSGeneticAlgorithm1.SelectionMethod)));
Memo1.Lines.Add('Number of generations:' + IntToStr(Generation));
Memo1.Lines.Add('Fittest Individual:' + FittestIndividual.Bits.ToString);
Memo1.Lines.Add(' Score:' + FloatToStr(RSGeneticAlgorithm1.FittestIndividual.Fitness));
Memo1.Lines.Add('Avg Fitness:' + FloatToStr(AvgFitness));
Memo1.Lines.Add('Min Fitness:' + FloatToStr(MinFitness));
Memo1.Lines.Add('Max Fitness:' + FloatToStr(MaxFitness));
if MaxFitness = FitnessCutoff then
for i := 0 to RSGeneticAlgorithm1.Genes.Count - 1 do
begin
sgChessBoard.Cols[i].Clear;
sgChessBoard.Cells[i, RSGeneticAlgorithm1.Genes[i].AsInteger[RSGeneticAlgorithm1.FittestIndividual.Index]] := 'Q';
end;
end;
end;
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