%% 該函數用于演示基于蟻群算法的三維路徑規劃算法
%% 清空環境
clc
clear
%% 數據初始化
%下載數據
load HeightData HeightData
%網格劃分
LevelGrid=10;
PortGrid=21;
%起點終點網格點
starty=10;starth=4;
endy=8;endh=5;
m=1;
%算法參數
PopNumber=10; %種群個數
BestFitness=[]; %最佳個體
%初始信息素
pheromone=ones(21,21,21);
%% 初始搜索路徑
[path,pheromone]=searchpath(PopNumber,LevelGrid,PortGrid,pheromone, ...
HeightData,starty,starth,endy,endh);
fitness=CacuFit(path); %適應度計算
[bestfitness,bestindex]=min(fitness); %最佳適應度
bestpath=path(bestindex,:); %最佳路徑
BestFitness=[BestFitness;bestfitness]; %適應度值記錄
%% 信息素更新
rou=0.2;
cfit=100/bestfitness;
for i=2:PortGrid-1
pheromone(i,bestpath(i*2-1),bestpath(i*2))= ...
(1-rou)*pheromone(i,bestpath(i*2-1),bestpath(i*2))+rou*cfit;
end
%% 循環尋找最優路徑
for kk=1:100
%% 路徑搜索
[path,pheromone]=searchpath(PopNumber,LevelGrid,PortGrid,...
pheromone,HeightData,starty,starth,endy,endh);
%% 適應度值計算更新
fitness=CacuFit(path);
[newbestfitness,newbestindex]=min(fitness);
if newbestfitness<bestfitness
bestfitness=newbestfitness;
bestpath=path(newbestindex,:);
end
BestFitness=[BestFitness;bestfitness];
%% 更新信息素
cfit=100/bestfitness;
for i=2:PortGrid-1
pheromone(i,bestpath(i*2-1),bestpath(i*2))=(1-rou)* ...
pheromone(i,bestpath(i*2-1),bestpath(i*2))+rou*cfit;
end
end
%% 最佳路徑
for i=1:21
a(i,1)=bestpath(i*2-1);
a(i,2)=bestpath(i*2);
end
figure(1)
x=1:21;
y=1:21;
[x1,y1]=meshgrid(x,y);
mesh(x1,y1,HeightData)
axis([1,21,1,21,0,2000])
hold on
k=1:21;
plot3(k(1)',a(1,1)',a(1,2)'*200,'--o','LineWidth',2,...
'MarkerEdgeColor','k',...
'MarkerFaceColor','g',...
'MarkerSize',10)
plot3(k(21)',a(21,1)',a(21,2)'*200,'--o','LineWidth',2,...
'MarkerEdgeColor','k',...
'MarkerFaceColor','g',...
'MarkerSize',10)
text(k(1)',a(1,1)',a(1,2)'*200,'S');
text(k(21)',a(21,1)',a(21,2)'*200,'T');
xlabel('km','fontsize',12);
ylabel('km','fontsize',12);
zlabel('m','fontsize',12);
title('三維路徑規劃空間','fontsize',12)
set(gcf, 'Renderer', 'ZBuffer')
hold on
plot3(k',a(:,1)',a(:,2)'*200,'--o')
%% 適應度變化
figure(2)
plot(BestFitness)
title('最佳個體適應度變化趨勢')
xlabel('迭代次數')
ylabel('適應度值')
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