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224 <strong>MATLAB</strong> CODE %_______________________________________________________ % Iterate through generations while iga
temp=pop(row1,col1); pop(row1,col1)=pop(row1,col2); pop(row1,col2)=temp; im(ic)=row1; end cost=feval(ff,pop); %_______________________________________________________ % Sort the costs and associated parameters part=pop; costt=cost; [cost,ind]=sort(cost); pop=pop(ind,:); %_______________________________________________________ % Do statistics minc(iga)=min(cost); meanc(iga)=mean(cost); end %iga PROGRAM 5: PERMUTATION GENETIC ALGORITHM 225 %_______________________________________________________ % Displays the output day=clock; disp(datestr(datenum(day(1),day(2),day(3),day(4),day( 5),day(6)),0)) disp([‘optimized function is ‘ ff]) format short g disp([‘popsize = ‘ num2str(popsize) ‘ mutrate = ‘ num2str(mutrate) ‘ # par = ‘ num2str(npar)]) disp([‘ best cost=’ num2str(cost(1))]) disp([‘best solution’]) disp([num2str(pop(1,:))]) figure(2) iters=1:maxit; plot(iters,minc,iters,meanc,’––’); xlabel(‘generation’);ylabel(‘cost’); figure(1);plot([x(pop(1,:)) x(pop(1,1))],[y(pop(1,:)) y(pop(1,1))],x,y,’o’);axis square
Page 1 and 2: APPENDIX II MATLAB Code MATLAB is a
Page 3 and 4: PROGRAM I: BINARY GENETIC ALGORTHIM
Page 5 and 6: PROGRAM 2: CONVERTS BINARY CHROMOSO
Page 7 and 8: PROGRAM 3: CONTINUOUS GENETIC ALGOR
Page 9 and 10: figure(24) iters=0:length(minc)-1;
Page 11 and 12: ma(ib)=picks(pt(ib),ib); end picks=
Page 13: PROGRAM 5: PERMUTATION GENETIC ALGO
Page 17 and 18: npar = 2; % Dimension of the proble
Page 19 and 20: PROGRAM 8: ANT COLONY OPTIMIZATION
Page 21 and 22: [tour,dist] figure(1) plot(xcity(to

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