1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
|
clear close clc
t0 = clock;
load sj.txt
x=sj(:,1:2:8); x=x(:);
y=sj(:,2:2:8); y=y(:);
sj=[x y]; d1=[70,40];
sj0=[d1;sj;d1]; sj=sj0*pi/180;
d=zeros(102);
for i=1:101
for j=i+1:102
temp=cos(sj(i,1)-sj(j,1))*cos(sj(i,2))*cos(sj(j,2))+sin(sj(i,2))*sin(sj(j,2));
d(i,j)=6370*acos(temp);
end
end
d=d+d';
n = size(sj0,1);
D = d;
m = 120;
alpha = 1;
beta = 5;
vol = 0.2;
Q = 10;
Heu_F = 1./D;
Tau = ones(n,n);
Table = zeros(m,n);
iter = 1;
iter_max = 50;
Route_best = zeros(iter_max,n);
Length_best = zeros(iter_max,1);
Length_ave = zeros(iter_max,1);
Limit_iter = 0;
while iter <= iter_max
start = zeros(m,1);
for i = 1:m
temp = randperm(n);
start(i) = temp(1);
end
Table(:,1) = start;
citys_index = 1:n;
for i = 1:m
for j = 2:n
tabu = Table(i,1:(j - 1));
allow_index = ~ismember(citys_index,tabu);
allow = citys_index(allow_index);
P = allow;
for k = 1:length(allow)
P(k) = Tau(tabu(end),allow(k))^alpha * Heu_F(tabu(end),allow(k))^beta;
end
P = P/sum(P);
Pc = cumsum(P);
target_index = find(Pc >= rand);
target = allow(target_index(1));
Table(i,j) = target;
end
end
Length = zeros(m,1);
for i = 1:m
Route = Table(i,:);
for j = 1:(n - 1)
Length(i) = Length(i) + D(Route(j),Route(j + 1));
end
Length(i) = Length(i) + D(Route(n),Route(1));
end
if iter == 1
[min_Length,min_index] = min(Length);
Length_best(iter) = min_Length;
Length_ave(iter) = mean(Length);
Route_best(iter,:) = Table(min_index,:);
Limit_iter = 1;
else
[min_Length,min_index] = min(Length);
Length_best(iter) = min(Length_best(iter - 1),min_Length);
Length_ave(iter) = mean(Length);
if Length_best(iter) == min_Length
Route_best(iter,:) = Table(min_index,:);
Limit_iter = iter;
else
Route_best(iter,:) = Route_best((iter-1),:);
end
end
Delta_Tau = zeros(n,n);
for i = 1:m
for j = 1:(n - 1)
Delta_Tau(Table(i,j),Table(i,j+1)) = Delta_Tau(Table(i,j),Table(i,j+1)) + Q/Length(i);
end
Delta_Tau(Table(i,n),Table(i,1)) = Delta_Tau(Table(i,n),Table(i,1)) + Q/Length(i);
end
Tau = (1-vol) * Tau + Delta_Tau;
iter = iter + 1;
Table = zeros(m,n);
end
[Shortest_Length,index] = min(Length_best);
Shortest_Route = Route_best(index,:);
Time_Cost=etime(clock,t0);
disp(['最短距离:' num2str(Shortest_Length)]);
disp(['最短时间:' num2str(Shortest_Length/1000) '小时']);
disp(['收敛迭代次数:' num2str(Limit_iter)]);
disp(['程序执行时间:' num2str(Time_Cost) '秒']);
figure(1)
plot(x,y,'bO')
hold on
plot(70,40,'p',...
'MarkerSize',10,...
'MarkerEdgeColor','b',...
'MarkerFaceColor','r')
hold on
plot([sj0(Shortest_Route,1);sj0(Shortest_Route(1),1)],...
[sj0(Shortest_Route,2);sj0(Shortest_Route(1),2)],'o-');
grid on
hold off
xlabel('经度')
ylabel('纬度')
title(['ACA最优化侦查路线(侦查时间:' num2str(Shortest_Length/1000) '小时)'])
figure(2)
plot(1:iter_max,Length_best/1000,'b')
legend('侦查最短时间')
xlabel('迭代次数')
ylabel('时间')
title('算法收敛轨迹')
|
