clear
clc
%生成初始解
sol_new2=1;%(1)解空间(初始解)
sol_new1=2-sol_new2^2;
sol_current1 = sol_new1;
sol_best1 = sol_new1;
sol_current2 = sol_new2;
sol_best2 = sol_new2;
E_current = inf;
E_best = inf;
rand('state',sum(clock)); %初始化随机数发生器
t=90; %初始温度
tf=89.9; %结束温度
a = 0.99; %温度下降比例
while t>=tf%(7)结束条件
for r=1:1000 %退火次数
%产生随机扰动(3)新解的产生
sol_new2=sol_new2+rand*0.2;
sol_new1=2-sol_new2^2;
%检查是否满足约束
if sol_new1^2-sol_new2>=0 && -sol_new1-sol_new2^2+2==0 && sol_new1>=0 &&sol_new2>=0
else
sol_new2=rand*2;
sol_new1=2-sol_new2^2;
continue;
end
%退火过程
E_new=sol_new1^2+sol_new2^2+8;%(2)目标函数
if E_new<E_current%(5)接受准则
E_current=E_new;
sol_current1=sol_new1;
sol_current2=sol_new2;
if E_new<E_best
%把冷却过程中最好的解保存下来
E_best=E_new;
sol_best1=sol_new1;
sol_best2=sol_new2;
end
else
if rand<exp(-(E_new-E_current)/t)%(4)代价函数差
E_current=E_new;
sol_current1=sol_new1;
sol_current2=sol_new2;
else
sol_new1=sol_current1;
sol_new2=sol_current2;
end
end
plot(r,E_best,'*')
hold on
end
t=t*a;%(6)降温
end
disp('最优解为:')
disp(sol_best1)
disp(sol_best2)
disp('目标表达式的最小值等于:')
disp(E_best)
---------------------------------
function len=computer_tour(city,n) %计算路线总长度,每个城市只计算和下家城市之间的距离。
len=0;
for i=1:n-1
len=len+sqrt((city(i).x-city(i+1).x)^2+(city(i).y-city(i+1).y)^2);
end
len=len+sqrt((city(n).x-city(1).x)^2+(city(n).y-city(1).y)^2);
end
------------------------------------
function city=perturb_tour(city,n)
%随机置换两个不同的城市的坐标
%产生随机扰动
p1=floor(1+n*rand());
p2=floor(1+n*rand());
while p1==p2
p1=floor(1+n*rand());
p2=floor(1+n*rand());
end
%exchange the random two cities
tmp=city(p1);
city(p1)=city(p2);
city(p2)=tmp;
end
------------------------
function netplot(city,n) %连线各城市,将路线画出来
hold on;
for i=1:n-1
plot(city(i).x,city(i).y,'r*');
line([city(i).x city(i+1).x],[city(i).y city(i+1).y]); %只连线当前城市和下家城市
end
plot(city(n).x,city(n).y,'r*');
line([city(n).x city(1).x],[city(n).y city(1).y]); %最后一家城市连线第一家城市
hold off;
end