I have a problem in Julia JuMP and I would really appreciate some help. I am currently trying to initialize a variable that I called X.
X represents the quantity of demand element e satisfied from production in block t at Machine n.
If I look into the model formulation I can see that n is element of N, e is element of E(n) and t is element of T(e).
we have 2 Machines so N = 2.
E(n), and T(e) should look something like this:
E(n) is set of demand elements e that can be produced on Machine 1 or 2
En = [[1, 2, 3, 4, 5, 6, 7, 8, 9], #Machine 1
[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12,...]] #Machine 2
T(e) represents the production periods for each of the demand elements
Te = [[1,2,3,4,5,6,7,8], # demand element 1
[1,2,3,4,5,6,7,8], # 2
[1,2,3,4,5,6,7,8], # 3
[1,2,3,4,5,6,7,8], # etc.
[1,2,3,4,5,6,7,8],
[1,2,3,4,5,6,7,8],
[1,2,3,4,5,6,7,8],
[1,2,3,4,5,6,7,8],
[1,2,3,4,5,6,7,8],
[1,2,3,4,5,6,7,8],
[1,2,3,4,5,6,7,8],
[1,2,3,4,5,6,7,8],
[1,2,3,4,5,6,7,8],
[1,2,3,4,5,6,7,8,9,10,11,12],
[1,2,3,4,5,6,7,8,9,10,11,12],
...
...
...]]
Now I want to initialize X as follows:
**@variable(MO, X[1:N, 1:En[1:N]], 1:Te[1:E] >= 0);**
But I unfortunately get the error code: MethodError: no method matching (::Colon)(::Int64, ::Vector{Vector{Int64}})
I unfortunately don't have too much experience with Julia so I would be really grateful for any help or hints how I can properly initialize X without getting this error.
I tried different ways to define the ranges of n,e and t, but I always get errors.
@variable(MO, X[1:N, 1:En[1:N]], 1:Te[1:E] >= 0)
You cannot write 1:En[1:N] because En[1:N] is a vector.
julia> x = [1, 2, 3]
3-element Vector{Int64}:
1
2
3
julia> 1:x
ERROR: MethodError: no method matching (::Colon)(::Int64, ::Vector{Int64})
Closest candidates are:
You also have some brackets in the wrong place. Did you mean instead:
@variable(MO, X[n=1:N, e=En[n], Te[e]] >= 0)
Here's an example:
julia> N = 2
2
julia> En = [ [1, 2], [1, 2, 3] ]
2-element Vector{Vector{Int64}}:
[1, 2]
[1, 2, 3]
julia> Te = [ [1], [1,2], [1,2,3,4] ]
3-element Vector{Vector{Int64}}:
[1]
[1, 2]
[1, 2, 3, 4]
julia> model = Model()
A JuMP Model
Feasibility problem with:
Variables: 0
Model mode: AUTOMATIC
CachingOptimizer state: NO_OPTIMIZER
Solver name: No optimizer attached.
julia> @variable(model, X[n=1:N, e=En[n], Te[e]] >= 0)
JuMP.Containers.SparseAxisArray{VariableRef, 3, Tuple{Int64, Int64, Int64}} with 10 entries:
[1, 1, 1] = X[1,1,1]
[1, 2, 1] = X[1,2,1]
[1, 2, 2] = X[1,2,2]
[2, 1, 1] = X[2,1,1]
[2, 2, 1] = X[2,2,1]
[2, 2, 2] = X[2,2,2]
[2, 3, 1] = X[2,3,1]
[2, 3, 2] = X[2,3,2]
[2, 3, 3] = X[2,3,3]
[2, 3, 4] = X[2,3,4]
julia> X[2, 3, 2]
X[2,3,2]