www.gusucode.com > 用蚁群算法解决TSP问题，其中有基本蚁群，蚁密系统，还有自己提出的改进算法，自带GUI界面 > 用蚁群算法解决TSP问题，其中有基本蚁群，蚁密系统，还有自己提出的改进算法，自带GUI界面/Main/ACS_main.m

    clear all;
clc;
tic;
%城市数据
%data=load('ulysses16.txt');
%data=load('ulysses22.txt');
%data=load('oliver30.txt');
data=load('att48.txt');
%data=load('eil51.txt');
%data=load('eil76.txt');
%data=load('eil101.txt');
%data=load('ch130.txt');
%data=load('ch150.txt');
%data=load('rat195.txt');
%data=load('tsp225.txt');
X=data(:,2);                                               %城市横坐标
Y=data(:,3);                                               %城市纵坐标
%AS算法参数
tau=1.16e-4;                                                 %初始信息素量
ant_num=15;                                                %蚂蚁数目
iter_num=200;                                              %算法迭代次数
pher_evap_rate=0.5;                                        %信息素蒸发速率
pher_effe_rate=1;                                          %信息素系数
heur_effe_rate=3;                                          %启发式信息系数
cand_length=20;                                             %最近邻列表长度
para_q=0.9;                                                %伪随机比例参数
psi=0.1;                                                   %局部信息素更新参数
%计算城市之间的距离和最近邻列表
if cand_length==0
   [dist,city_num]=dist_cand(X,Y);
else
   [dist,city_num,cand_list]=dist_cand(X,Y,cand_length);
end
%初始化信息素矩阵和计算信息素与启发式信息联合矩阵
pher=(ones(city_num)-eye(city_num))*tau;
choice_info=calc_info(pher_effe_rate,heur_effe_rate,pher,dist);
%蚂蚁构建路径
for order=1:iter_num
    %每一次迭代开始时清楚蚂蚁记录并随机初始化蚂蚁起点城市
    ant=clear_fisttour(ant_num,city_num);
    %采用并行方式构建蚂蚁剩余部分路径
    for step=2:city_num
        for i=1:ant_num
            pres_city =ant(i).tour(step-1);                
            rand_q=rand;     
            if cand_length==0                               %未使用候选列表
                if rand_q<=para_q
                    next_city=acs_next_tour(pres_city,city_num,choice_info,ant(i));
                else
                    next_city=as_next_tour(city_num,choice_info,pres_city,ant(i));
                end   
            else                                            %使用候选列表
                if rand_q<=para_q
                     next_city=acs_next_tour(pres_city,city_num,choice_info,ant(i));
                    %next_city=acs_cand_next_tour(pres_city,city_num,choice_info,cand_length,cand_list,ant(i));
                else
                    next_city=as_cand_next_tour(cand_list,cand_length,city_num,pres_city,choice_info,ant(i));
                end
            end
            %将下一访问城市添加到路径和记录表中
            ant(i).tour(step)=next_city;                  
            ant(i).visited(next_city)=1;                   
            %局部信息素更新并更改信息素与启发式信息联合矩阵
            pher(pres_city,next_city)=(1-psi)*pher(pres_city,next_city)+psi*tau;
            pher(next_city,pres_city)=pher(pres_city,next_city);    
            choice_info(pres_city,next_city)=pher(pres_city,next_city)*(1/dist(pres_city,next_city))^heur_effe_rate;
            choice_info(next_city,pres_city)=choice_info(pres_city,next_city);
       end
    end
    %计算每一只蚂蚁的路径长度和当前迭代最优路径
    [iter_best,ant]=tourlength_iterbest(ant_num,city_num,dist,ant);
    %求得迭代至今最优路径
    if order==1
        glob_best.tour=iter_best.tour;
        glob_best.length=iter_best.length;
        glob_best.found=1;
        glob_best.time=toc;
    elseif   iter_best.length<glob_best.length
        glob_best.tour=iter_best.tour;
        glob_best.length=iter_best.length;
        glob_best.found=order;
        glob_best.time=toc;
    end
    %全局信息素更新
    pher=acs_glob_pher_update(glob_best,pher_evap_rate,city_num,pher); 
    figure(1)
    for i=1:city_num+1
        m=glob_best.tour(i);
        p(i)=X(m);
        q(i)=Y(m);
    end
    scatter(X,Y,'.');box on;
    hold on;
    plot(p,q);
    title(num2str(glob_best.length));
    hold off;
end
disp(['蚁群系统运行时间为：' num2str(toc) '秒']);
disp(['蚁群系统最优路径长度为：' num2str(glob_best.length) ]);
disp(['蚁群系统求得最优路径时间为：' num2str(glob_best.time) '秒']);
disp(['蚁群系统最优路径的迭代次数为：' num2str(glob_best.found)]);