Updated models with ≤ syntax

Author: Azzaare

src/assignment.jl

@@ -1,7 +1,7 @@
 function qap(n, W, D, ::Val{:JuMP})
     model = JuMP.Model(CBLS.Optimizer)
 
-    @variable(model, X[1:n], DiscreteSet(1:n))
+    @variable(model, 1 ≤ X[1:n] ≤ n, Int)
     @constraint(model, X in AllDifferent())
 
     Σwd = p -> sum(sum(W[p[i], p[j]] * D[i, j] for j in 1:n) for i in 1:n)

src/golomb.jl

@@ -33,9 +33,7 @@ end
 function golomb(n, L, ::Val{:JuMP})
     m = JuMP.Model(CBLS.Optimizer)
 
-    @variable(m, X[1:n], DiscreteSet(0:L))
-
-    # @constraint(m, X[1] in AllEqualParam(0)) # first mark at 0
+    @variable(m, 1 ≤ X[1:n] ≤ L, Int)
 
     @constraint(m, X in AllDifferent()) # different marks
     @constraint(m, X in Ordered()) # for output convenience, keep them ordered

src/magic_square.jl

@@ -4,7 +4,7 @@ function magic_square(n, ::Val{:JuMP})
     magic_constant = n * (N + 1) / 2
     Σeq = x -> sum(x) == magic_constant
 
-    @variable(model, X[1:n, 1:n], DiscreteSet(1:N))
+    @variable(model, 1 ≤ X[1:n, 1:n] ≤ N, Int)
     @constraint(model, vec(X) in AllDifferent())
 
     for i in 1:n

src/n_queens.jl

@@ -1,23 +1,21 @@
 function n_queens(n, ::Val{:JuMP})
     model = JuMP.Model(CBLS.Optimizer)
 
-    @variable(model, queens[1:n], DiscreteSet(1:n))
-    @constraint(model, queens in AllDifferent())
+    @variable(model, 1 ≤ Q[1:n] ≤ n, Int)
+    @constraint(model, Q in AllDifferent())
 
-    for i in 1:n
-        for j in i+1:n
-            @constraint(model, [queens[i],queens[j]] in Predicate(x -> x[1] != x[2]))
-            @constraint(model, [queens[i],queens[j]] in Predicate(x -> (x[1] != x[2]+i-j)))
-            @constraint(model, [queens[i],queens[j]] in Predicate(x -> (x[1] != x[2]+j-i)))
-        end
+    for i in 1:n, j in i + 1:n
+        @constraint(model, [Q[i],Q[j]] in Predicate(x -> x[1] != x[2]))
+        @constraint(model, [Q[i],Q[j]] in Predicate(x -> x[1] != x[2] + i - j))
+        @constraint(model, [Q[i],Q[j]] in Predicate(x -> x[1] != x[2] + j - i))
     end
 
-    return model, queens
+    return model, Q
 end
 
 """
     n_queens(n; modeler = :JuMP)
 
 Create a model for the n-queens problem with `n` queens. The `modeler` argument accepts :JuMP (default), which refer to the JuMP model.
 """
-n_queens(n; modeler = :JuMP) = n_queens(n, Val(modeler))
+n_queens(n; modeler=:JuMP) = n_queens(n, Val(modeler))

src/sudoku.jl

@@ -69,16 +69,12 @@ function sudoku(n, start, ::Val{:JuMP})
     N = n^2
     m = JuMP.Model(CBLS.Optimizer)
 
-    if isnothing(start)
-        @variable(m, X[1:N, 1:N], DiscreteSet(1:N))
-    else
-        @variable(m, X[1:N, 1:N])
+    @variable(m, 1 ≤ X[1:N, 1:N] ≤ N, Int)
+    if !isnothing(start)
         for i in 1:N, j in 1:N
             v_ij = start[i,j]
             if 1 ≤ v_ij ≤ N
                 @constraint(m, X[i,j] == v_ij)
-            else
-                @constraint(m, X[i,j] in DiscreteSet(1:N))
             end
         end
     end