I have the following model.

array[int] of float: weight;
set of int: nodes = index_set(weight);
int: n = max(nodes);

array[nodes] of var 1..n: segment_start;
array[nodes] of var 0..0: segment_length;

function var float: segment_weight(int: s) = 
    (i in segment_start[s]..(segment_start[s] + segment_length[s] - 1) where i <= n)

var float: mass = sum (s in nodes) (segment_weight(s));

solve satisfy;

The model is unsatisfiable according to MiniZinc, however, when I get rid of the variable mass, a solution is found. How can an existence of a variable (i.e. not a constraint) influence whether a model is solvable? Does it have sometime to do with optional types? And how do I fix this?

  • $\begingroup$ The issue may be with your data (which is not shown here). $\endgroup$
    – prubin
    Commented Dec 2, 2021 at 17:06
  • $\begingroup$ I can try to modify the data on my side and see how it affects the outcome. The question still stands, though; how can adding a variable change the satisfiability? $\endgroup$
    – Eugleo
    Commented Dec 2, 2021 at 18:56
  • $\begingroup$ One possibility would be that something in the data makes segment_weight(s) undefined for a specific value of s. $\endgroup$
    – prubin
    Commented Dec 2, 2021 at 20:20

1 Answer 1


It seems you ran into an issue in the MiniZinc compiler. Running with weight = [1,2,3]; under the current release (2.5.5) does indeed give UNSAT (even though it shouldn't):

$ minizinc --solver cbc ./should_work.mzn

However, if you run using the current develop branch of MiniZinc then it does give an asnwer:

$ ./github.com/MiniZinc/libminizinc/build/Debug/minizinc --solver cbc ./should_work.mzn
segment_start = [1, 1, 1];
segment_length = [0, 0, 0];

I do not know exactly where this issue was solved, but I can say that a new release of MiniZinc will soon be available that should include this fix. In the meantime you could already use the develop branch of MiniZinc.


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