I have a MILP formulation. The variable is a 3 dimensional binary matrix. I know lots of it’s optimal values. For example suppose A(20*20*100) is the variable. I know that in optimal solution the A(1,1,i) equals to zero. A(2,2,i) is zero too. and so on.

As the solving time is very important in my context so how can i explain to CVX that some variables are determined.

Why not use equality constraints?

You can specify the known values as constraints. For example,

```
A(1,1,:) == 0
A(2,2,:) == 0
```

Edit: this is what mcg is talking about.

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Yes, but you actually explained it, so thank you

Thanks a lot

Is it efficient? As execution time is very important for me does CVX interpret A(1,1,:)==0 as a constraint or set the value of A(1,1,:)?

If execution time is very important to you then CVX is not your tool, which is focused on saving the *modeler’s* time, not the computer’s time.

That said, CVX will interpret that constraint “efficiently”, by not generating a variable at all.

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