📄 sga.m
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% sga%% This script implements the Simple Genetic Algorithm described% in the examples section of the GA Toolbox manual.%% Author: Andrew Chipperfield% History: 23-Mar-94 file created NIND = 40; % Number of individuals per subpopulationsMAXGEN = 300; % maximum Number of generationsGGAP = .9; % Generation gap, how many new individuals are createdNVAR = 20; % Generation gap, how many new individuals are createdPRECI = 20; % Precision of binary representation% Build field descriptor FieldD = [rep([PRECI],[1, NVAR]); rep([-512;512],[1, NVAR]);... rep([1; 0; 1 ;1], [1, NVAR])];% Initialise population Chrom = crtbp(NIND, NVAR*PRECI);% Reset counters Best = NaN*ones(MAXGEN,1); % best in current population gen = 0; % generational counter% Evaluate initial population ObjV = objfun1(bs2rv(Chrom,FieldD));% Track best individual and display convergence Best(gen+1) = min(ObjV); plot(log10(Best),'ro');xlabel('generation'); ylabel('log10(f(x))'); text(0.5,0.95,['Best = ', num2str(Best(gen+1))],'Units','normalized'); drawnow; % Generational loop while gen < MAXGEN, % Assign fitness-value to entire population FitnV = ranking(ObjV); % Select individuals for breeding SelCh = select('sus', Chrom, FitnV, GGAP); % Recombine selected individuals (crossover) SelCh = recombin('xovsp',SelCh,0.7); % Perform mutation on offspring SelCh = mut(SelCh); % Evaluate offspring, call objective function ObjVSel = objfun1(bs2rv(SelCh,FieldD)); % Reinsert offspring into current population [Chrom ObjV]=reins(Chrom,SelCh,1,1,ObjV,ObjVSel); % Increment generational counter gen = gen+1; % Update display and record current best individual Best(gen+1) = min(ObjV); plot(log10(Best),'ro'); xlabel('generation'); ylabel('log10(f(x))'); text(0.5,0.95,['Best = ', num2str(Best(gen+1))],'Units','normalized'); drawnow; end % End of GA
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