仿真的多目标优化(蚁群算法在旅行商问题中的应用)

tabu_list=zeros(m,n); end

%输出结果，绘制图形

position=find(length_best==min(length_best)); shortest_path=routh_best(position(1),:) shortest_length=length_best(position(1)) %绘制最短路径 figure(1)

set(gcf,'Name','Ant Colony Optimization——Figure of shortest_path','Color','r') N=length(shortest_path);

scatter(C(:,1),C(:,2),50,'filled'); hold on

plot([C(shortest_path(1),1),C(shortest_path(N),1)],[C(shortest_path(1),2),C(shortest_path(N),2)]) set(gca,'Color','g') hold on for i=2:N

plot([C(shortest_path(i-1),1),C(shortest_path(i),1)],[C(shortest_path(i-1),2),C(shortest_path(i),2)]) hold on end

%绘制每次循环最短路径长度和平均路径长度 figure(2)

set(gcf,'Name','Ant Colony Optimization——Figure of length_best and length_average','Color','r') plot(length_best,'r') set(gca,'Color','g') hold on

plot(length_average,'k')

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