以set +公式的形式初始化GAMS中的决策变量会产生错误

问题描述

我正在尝试使用GAMS为问题建模.我有2个问题:

I am trying to model a problem using GAMS. I have 2 questions:

1)如何初始化决策值P?它应该采用以下格式

1) How to initialize the decesion value P? it supose to be in the following form

P(I)/

i1 25

i2 33/

2)我正在尝试像

SINR(I)= e = hh(I)* P(I)/sqrsigma)+ sum(I，H(J，I)* P(I));

SINR(I) =e= hh(I)*P(I) / sqr(sigma)+sum(I,H(J,I)*P(I));

但是，我总是得到一个错误，即该设置已经是控制器或域问题.我该如何解决这个问题?

However, I got always an erro either the set is already controller or domain isssues. How can I solve this problem?

部分代码

我的用户数/i1，i2/

I number of users /i1,i2/

J个用户干扰/j1，j2/

J users to interfer with /j1,j2/

迭代次数/1/;

参数

CP(I) circuit power per user  /

i1  10

i2  10 /
hh(I)  channel quality  /    i1  48    i2  106 /
Sigma    Noise              /0.0057/
tol      tolerence value    /0.01/
minRate  minimum rate /0.1/

maxiter max number of iterations /3/   ;

Table H(J,I) interference value

>        i1          i2
>
>  j1    0         18.8030
> 
>  j2    8.9555         0 

;>

P(I)

F

lambda

SINR(I)

b(I)

a(I)

方程式Objectivefun，SINRFUN，lambdaFUN，RateFUN，afun，bfun， nonlconfun;

equations Objectivefun, SINRFUN, lambdaFUN, RateFUN, afun, bfun, nonlconfun;

SINRFUN(I).. SINR(I)= e = hh(I)* P(I)/ sqr(sigma)+ sum(I，H(J，I)* P(I));

SINRFUN(I).. SINR(I) =e= hh(I)*P(I) / sqr(sigma)+sum(I,H(J,I)*P(I));

先谢谢您.

推荐答案

语句

SINRFUN(I).. SINR(I) =e= hh(I)*P(I) / sqr(sigma)+sum(I,H(J,I)*P(I));

有一个问题，我们在i上有一个隐式循环，然后在同一i上的和内.这在数学上不是很好定义.因此，您可以执行以下操作:

has a problem we have an implicit loop over i and then inside a sum over the same i. This is mathematically not very well defined. So you could do something like:

alias(i,ii);
SINRFUN(I).. SINR(I) =e= hh(I)*P(I) / sqr(sigma)+sum(ii,H(J,ii)*P(ii));

您可以使用赋值语句初始化P(i):

You can initialize P(i) with an assignment statement:

parameter initp(i) /i1 25, i2 33/;
p.L(i) = initp(i);

.L表示我们为变量分配了级别值(其他可能性是诸如.lo，.up，.m之类的内容:有关更多信息，请参见文档-阅读一些文档可能对任何情况).

The .L means we assign to the level values of the variables (other possibilities are things like.lo, .up, .m: see the documentation for more information -- reading some docs may be beneficial in any case).

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