Hi. I’ve been struggling for nights with combinatorial optimization

Input = matrix with permutation.

Each row represents unit, and column means visit sequence for each place.

e.g) x = [ 1 2 3 4 ; 2 3 1 4 ; 3 1 2 4 ]

it means, First unit visits 1 first, and 2 3 4 in a row. Second unit visits 2 3 1 4

And also I made a function.

Based on markov chain, It calculate an expected complete time(=makespan).

function name is allinone(x). x is a matrix like above

My objective is to find an optimal x (visit sequence).

And if that is exist, I can calculate an expected complete time as well.

For this problem, I’ve searched for many packages, like JuMP, MHLib, ConstraintSolver, Combo(not available) and so on.

Based on that, I made a code like below.

```
using ConstraintSolver
const CS = ConstraintSolver
prio = [1 2 3 4;
2 3 1 4;
3 1 2 4]
function testing()
model = Model(CS.Optimizer)
@variable(model, 1 <= x[1:3,1:4] <= 4, Int)
for sqd = 1:3
@constraint(model, x[sqd,:] in CS.AllDifferent())
end
@objective(model, Min, allinone(x))
optimize!(model)
@show JuMP.value.(x)
end
testing()
```

But, When I put this, there is a error.

“MethodError: Cannot `convert`

an object of type VariableRef to an object of type Int64”

How can handle this error? Can I get some advice?

And I’m not sure that I could solve this problem even if I handle this error.

So, Would you got some recommendation for this problem?

Thank you for reading this, and hope some replies.