Please read the following post, and provide a minimum working example. If the warning is coming from your code, fix it. If the warning is coming from JuMP, upgrade to Julia 1.0.

using JuMP, Gurobi
my = Model(solver=GurobiSolver())
@variable(my, x[1:2]>=0, Int)
@constraint(my, x[1] == x[2])
@objective(my, Min, x[1] + x[2])
status = solve(my)
print(my)

┌ Warning: Deprecated syntax `implicit assignment to global variable `#2781###740``.
│ Use `global #2781###740` instead.
└ @ none:0
┌ Warning: Deprecated syntax `implicit assignment to global variable `#2781###740``.
│ Use `global #2781###740` instead.
└ @ none:0
Academic license - for non-commercial use only
Optimize a model with 1 rows, 2 columns and 2 nonzeros
Variable types: 0 continuous, 2 integer (0 binary)
Coefficient statistics:
Matrix range [1e+00, 1e+00]
Objective range [1e+00, 1e+00]
Bounds range [0e+00, 0e+00]
RHS range [0e+00, 0e+00]
Found heuristic solution: objective 0.0000000
Explored 0 nodes (0 simplex iterations) in 0.00 seconds
Thread count was 1 (of 4 available processors)
Solution count 1: 0
Optimal solution found (tolerance 1.00e-04)
Best objective 0.000000000000e+00, best bound 0.000000000000e+00, gap 0.0000%
Min x[1] + x[2]
Subject to
x[1] - x[2] == 0
x[i] >= 0, integer, for all i in {1,2}