scale.sga

Pascal Programs Printed in GENETIC ALGORITHMS IN SEARCH, OPTIMIZATION, AND MACHINE LEARNING by Da

{ scale.sga: contains prescale, scale, scalepop for scaling fitnesses }

procedure prescale(umax, uavg, umin:real; var a, b:real);
{ Calculate scaling coefficients for linear scaling }
const fmultiple = 2.0;     { Fitness multiple is 2 }
var   delta:real;          { Divisor }
begin
 if umin > (fmultiple*uavg - umax) / (fmultiple - 1.0) { Non-negative test }
     then begin  { Normal Scaling }
       delta := umax - uavg;
       a := (fmultiple - 1.0) * uavg / delta;
       b := uavg * (umax - fmultiple*uavg) / delta;
      end else begin   { Scale as much as possible }
        delta := uavg - umin;
        a := uavg / delta;
        b := -umin * uavg / delta;
       end;
end;

function scale(u, a, b:real):real;
{ Scale an objective function value }
begin  scale := a * u + b end;

procedure scalepop(popsize:integer; var max, avg, min, sumfitness:real;
                   var pop:population);
{ Scale entire population }
var j:integer;
    a, b:real;    { slope & intercept for linear equation }
begin
 prescale(max, avg, min, a, b);  { Get slope and intercept for function }
 sumfitness := 0.0;
 for j := 1 to popsize do with pop[j] do begin
   fitness := scale(objective, a, b);
   sumfitness := sumfitness + fitness;
  end;
end;