Hi guys,

What do you recommend to do in this situation?

I have a set `M`

consisting of three separate sets of vectors of various size. In other words `M = [m_1, m_2, m_3] `

where `m_i`

are vectors of different sizes. For instance `m_1`

could be `1:10`

while `m_2 = 22:65`

and `m_3 = 100:123`

(these are separate, no intersection in their elements).

with that, there need to have a variable `x[i,j,m]`

to have some constraints as the following:

```
# N is a set which contains all net nodes
# x,z are variables
x[i,j,m] >= z[i,j] for all i,j in N and m in M
```

Now, we have another variables that are only defined on `m_i`

like `y[i,j,m_1]`

. So, at some points in some constraints, there’s only need to put condition over a subset of `M`

(not all of its components). Similar to the following:

```
#I'm not writing like julia-- more like math version
sum(x[i,j,m] for i in N) <= y[i, m] for all j in N and m in m_1
```

I did try to do this by:

```
@constraint(model, [j in N, m in m_1], sum( x[i,j,m] for i in N) <= y[i, m] )
```

This is not working though. Do you know how to do this? having a variables that can act both over the whole set `M`

and also act locally over just `m_1`

or just `m_2`

I’m not sure if the issue is variable either. What I need to find out is that how to have flexible variable `x`

that can handle `M`

and `m_1`

at the same time.

Thanks all!