请大神帮忙看个程序,,,
model:title Location problem;
sets:
demand/1..6/:a,b,d;
supply/1..2/:x,y,e;
link(demand,supply):c;
endsets
data:
!location for the demand(需求点位置);
a=1.25,8.75,0.5,5.75,3,7.25;
b=1.25,0.75,4.75,5,6.5,7.75;
!quatities of the demand and supply(供需量);
d=3,5,4,7,6,11;
e=20,20;
enddata
init:
!初始点;
x,y=5,1,2,7;
endinit
min=@sum(link(i,j):c(i,j)*(((x(i)-a(i))^2+(y(j)-b(i))^2)^(1/2));
@for(demand(i): @sum(supply(j):c(i,j))=d(i););(这里显示for使用错误)
@for(supply(j): @sum(demand(i):c(i,j))<e(j););
@for(supply:@free(x);@free(y););
end 求大神看看哪错了 model:
title Location problem;
sets:
demand/1..6/:a,b,d;
supply/1..2/:x,y,e;
link(demand,supply):c;
endsets
data:
!location for the demand(需求点位置);
a=1.25,8.75,0.5,5.75,3,7.25;
b=1.25,0.75,4.75,5,6.5,7.75;
!quatities of the demand and supply(供需量);
d=3,5,4,7,6,11;
e=20,20;
enddata
init:
!初始点;
x,y=5,1,2,7;
endinit
min=@sum(link(i,j):c(i,j)*(((x(i)-a(i))^2+(y(j)-b(i))^2)^(1/2));
@for(demand(i): @sum(supply(j):c(i,j))=d(i););
@for(supply(j): @sum(demand(i):c(i,j))<e(j););
@for(supply:@free(x);@free(y););
end 那个表情是自己碰到表情快捷键出来的{:soso_e101:} 我是这么写的,你可以参考下,结果是:85.26604
MODEL:
SETS:
GD/1..6/:X,Y,D;
LCH/A,B/:PX,PY,E;
LINKS(GD,LCH):C;
ENDSETS
DATA:
X=1.25 8.75 0.5 5.75 3 7.25;
Y=1.25 0.75 4.75 5 6.5 7.75;
D=3,5,4,7,6,11;
E=20,20;
ENDDATA
INIT:
PX=5.2083,5.2083;
PY=5.1597,5.1597;
ENDINIT
MIN=@SUM(LINKS(I,J):C(I,J)*((PX(J)-X(I))^2+(PY(J)-Y(I))^2)^(1/2));
@FOR(GD(I):@SUM(LCH(J):C(I,J))=D(I));
@FOR(LCH(J):@SUM(GD(I):C(I,J))<=E(J));
@FOR(LCH:@BND(0.5,PX,8.75));
@FOR(LCH:@BND(0.75,PY,7.75));
END
这个迭代初值是我通过某种方式算出来的,其实也没什么影响。
结果:
Local optimal solution found.
Objective value: 85.26604
Infeasibilities: 0.000000
Total solver iterations: 61
Variable Value Reduced Cost
X( 1) 1.250000 0.000000
X( 2) 8.750000 0.000000
X( 3) 0.5000000 0.000000
X( 4) 5.750000 0.000000
X( 5) 3.000000 0.000000
X( 6) 7.250000 0.000000
Y( 1) 1.250000 0.000000
Y( 2) 0.7500000 0.000000
Y( 3) 4.750000 0.000000
Y( 4) 5.000000 0.000000
Y( 5) 6.500000 0.000000
Y( 6) 7.750000 0.000000
D( 1) 3.000000 0.000000
D( 2) 5.000000 0.000000
D( 3) 4.000000 0.000000
D( 4) 7.000000 0.000000
D( 5) 6.000000 0.000000
D( 6) 11.00000 0.000000
PX( A) 3.254883 0.000000
PX( B) 7.250000 0.6335133E-06
PY( A) 5.652332 0.000000
PY( B) 7.750000 0.5438639E-06
E( A) 20.00000 0.000000
E( B) 20.00000 0.000000
C( 1, A) 3.000000 0.000000
C( 1, B) 0.000000 4.008540
C( 2, A) 0.000000 0.2051358
C( 2, B) 5.000000 0.000000
C( 3, A) 4.000000 0.000000
C( 3, B) 0.000000 4.487750
C( 4, A) 7.000000 0.000000
C( 4, B) 0.000000 0.5535090
C( 5, A) 6.000000 0.000000
C( 5, B) 0.000000 3.544853
C( 6, A) 0.000000 4.512336
C( 6, B) 11.00000 0.000000
Row Slack or Surplus Dual Price
1 85.26604 -1.000000
2 0.000000 -4.837363
3 0.000000 -7.158911
4 0.000000 -2.898893
5 0.000000 -2.578982
6 0.000000 -0.8851584
7 0.000000 0.000000
8 0.000000 0.000000
9 4.000000 0.000000
wujianjack2 发表于 2013-7-12 17:22 static/image/common/back.gif
我是这么写的,你可以参考下,结果是:85.26604
MODEL:
SETS:
谢谢了,请问那个迭代初值是用什么方法确定的:) 和子 发表于 2013-7-13 16:56 static/image/common/back.gif
谢谢了,请问那个迭代初值是用什么方法确定的
其实这个迭代初值没什么影响,你可以试下其它数据,个人觉得重点在于限定了PX,PY的取值范围,至于初值是怎么算的,也就不重要了。
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