MATLAB智能算法30个案例分析 源代码

MATLAB智能算法的源代码%% 清空环境 clc;clear %% 障碍物数据 position = load('barrier.txt'); plot([0,200],[0,200],'.'); hold on B = load('barrier.txt'); xlabel('km','fontsize',12) ylabel('km','fontsize',12) title('二维规划空间','fontsize',12) %% 描述起点和终点 S = [20,180]; T = [160,90]; plot([S(1),T(1)],[S(2),T(2)],'.'); % 图形标注 text(S(1)+2,S(2),'S'); text(T(1)+2,T(2),'T'); %% 描绘障碍物图形 fill(position(1:4,1),position(1:4,2),[0,0,0]); fill(position(5:8,1),position(5:8,2),[0,0,0]); fill(position(9:12,1),position(9:12,2),[0,0,0]); fill(position(13:15,1),position(13:15,2),[0,0,0]); % 下载链路端点数据 L = load('lines.txt'); %% 描绘线及中点 v = zeros(size(L)); for i=1:20 plot([position(L(i,1),1),position(L(i,2),1)],[position(L(i,1),2)... ,position(L(i,2),2)],'color','black','LineStyle','--'); v(i,:) = (position(L(i,1),:)+position(L(i,2),:))/2; plot(v(i,1),v(i,2),'*'); text(v(i,1)+2,v(i,2),strcat('v',num2str(i))); end %% 描绘可行路径 sign = load('matrix.txt'); [n,m]=size(sign); for i=1:n if i == 1 for k=1:m-1 if sign(i,k) == 1 plot([S(1),v(k-1,1)],[S(2),v(k-1,2)],'color',... 'black','Linewidth',2,'LineStyle','-'); end end continue; end for j=2:i if i == m if sign(i,j) == 1 plot([T(1),v(j-1,1)],[T(2),v(j-1,2)],'color',... 'black','Linewidth',2,'LineStyle','-'); end else if sign(i,j) == 1 plot([v(i-1,1),v(j-1,1)],[v(i-1,2),v(j-1,2)],... 'color','black','Linewidth',2,'LineStyle','-'); end end end end path = DijkstraPlan(position,sign); j = path(22); plot([T(1),v(j-1,1)],[T(2),v(j-1,2)],'color','yellow','LineWidth',3,'LineStyle','-.'); i = path(22); j = path(i); count = 0; while true plot([v(i-1,1),v(j-1,1)],[v(i-1,2),v(j-1,2)],'color','yellow','LineWidth',3,'LineStyle','-.'); count = count + 1; i = j; j = path(i); if i == 1 || j==1 break; end end plot([S(1),v(i-1,1)],[S(2),v(i-1,2)],'color','yellow','LineWidth',3,'LineStyle','-.'); count = count+3; pathtemp(count) = 22; j = 22; for i=2:count pathtemp(count-i+1) = path(j); j = path(j); end path = pathtemp; path = [1 9 8 7 13 14 12 22]; %% 蚁群算法参数初始化 pathCount = length(path)-2; %经过线段数量 pheCacuPara=2; %信息素计算参数 pheThres = 0.8; %信息素选择阈值 pheUpPara=[0.1 0.0003]; %信息素更新参数 qfz= zeros(pathCount,10); %启发值 phePara = ones(pathCount,10)*pheUpPara(2); %信息素 qfzPara1 = ones(10,1)*0.5; %启发信息参数 qfzPara2 = 1.1; %启发信息参数 m=10; %种群数量 NC=500; %循环次数 pathk = zeros(pathCount,m); %搜索结果记录 shortestpath = zeros(1,NC); %进化过程记录 %% 初始最短路径 dijpathlen = 0; vv = zeros(22,2); vv(1,:) = S; vv(22,:) = T; vv(2:21,:) = v; for i=1:pathCount-1 dijpathlen = dijpathlen + sqrt((vv(path(i),1)-vv(path(i+1),1))^2+(vv(path(i),2)-vv(path(i+1),2))^2); end LL = dijpathlen; %% 经过的链接线 lines = zeros(pathCount,4); for i = 1:pathCount lines(i,1:2) = B(L(path(i+1)-1,1),:); lines(i,3:4) = B(L(path(i+1)-1,2),:); end %% 循环搜索 for num = 1:NC %% 蚂蚁迭代寻优一次 for i=1:pathCount for k=1:m q = rand(); qfz(i,:) = (qfzPara2-abs((1:10)'/10-qfzPara1))/qfzPara2; %启发信息 if q<=pheThres%选择信息素最大值 arg = phePara(i,:).*(qfz(i,:).^pheCacuPara); j = find(arg == max(arg)); pathk(i,k) = j(1); else % 轮盘赌选择 arg = phePara(i,:).*(qfz(i,:).^pheCacuPara); sumarg = sum(arg); qq = (q-pheThres)/(1-pheThres); qtemp = 0; j = 1; while qtemp < qq qtemp = qtemp + (phePara(i,j)*(qfz(i,j)^pheCacuPara))/sumarg; j=j+1; end j=j-1; pathk(i,k) = j(1); end % 信息素更新 phePara(i,j) = (1-pheUpPara(1))*phePara(i,j)+pheUpPara(1)*pheUpPara(2); end end %% 计算路径长度 len = zeros(1,k); for k=1:m Pstart = S; Pend = lines(1,1:2) + (lines(1,3:4)-lines(1,1:2))*pathk(1,k)/10; for l=1:pathCount len(1,k) = len(1,k)+sqrt(sum((Pend-Pstart).^2)); Pstart = Pend; if l<pathCount Pend = lines(l+1,1:2) + (lines(l+1,3:4)-lines(l+1,1:2))*pathk(l+1,k)/10; end end Pend = T; len(1,k) = len(1,k)+sqrt(sum((Pend-Pstart).^2)); end %% 更新信息素 % 寻找最短路径 minlen = min(len); minlen = minlen(1); minant = find(len == minlen); minant = minant(1); % 更新全局最短路径 if minlen < LL LL = minlen; end % 更新信息素 for i=1:pathCount phePara(i,pathk(i,minant)) = (1-pheUpPara(1))* phePara(i,pathk(i,minant))+pheUpPara(1)*(1/minlen); end shortestpath(num) = minlen; end figure; plot(1:NC,shortestpath,'color','blue'); hold on % plot(1:NC,dijpathlen,'color','red'); ylabel('路径总长度'); xlabel('迭代次数');