If I `optimize!`

a model with GLPK, then add a constraint, I can still access the solution:

```
using JuMP, GLPK, Clp;
M = Model();
@variable M A[1:2] >= 0;
@constraint M limit1 sum(a for a in A) <= 1;
@objective M Max sum(a for a in A);
set_optimizer(M, GLPK.Optimizer);
optimize!(M);
@constraint M limit2 sum(a for a in A) <= 2;
value(M[:A][1])
1.0
```

But if I do the same thing in Clp, I get `OptimizeNotCalled()`

:

```
using JuMP, GLPK, Clp;
M = Model();
@variable M A[1:2] >= 0;
@constraint M limit1 sum(a for a in A) <= 1;
@objective M Max sum(a for a in A);
set_optimizer(M, Clp.Optimizer);
optimize!(M);
@constraint M limit2 sum(a for a in A) <= 2;
value(M[:A][1])
ERROR: OptimizeNotCalled()
```

Should this be consistent? Is it solver specific? Do we care?

(I had inadvertently been relying on GLPKâ€™s behaviour, but I can work with Clpâ€™s).

Thanks!

Geoff