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Constraint Programming Solver
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test/constraints/all_different/all_different_dc_test.exs
defmodule CPSolverTest.Constraint.AllDifferent.DC do
use ExUnit.Case, async: false
describe "AllDifferent" do
alias CPSolver.Constraint.AllDifferent.DC, as: AllDifferent
alias CPSolver.IntVariable
alias CPSolver.Constraint
alias CPSolver.Model
import CPSolver.Variable.View.Factory
test "all fixed" do
variables = Enum.map(1..5, fn i -> IntVariable.new(i) end)
model = Model.new(variables, [Constraint.new(AllDifferent, variables)])
{:ok, result} = CPSolver.solve(model)
assert hd(result.solutions) == [1, 2, 3, 4, 5]
assert result.statistics.solution_count == 1
end
test "reduction" do
minizinc_solutions = [[1, 2, 4, 5], [1, 2, 3, 4], [1, 2, 3, 5]]
variables = Enum.map([1, 1..2, 1..4, [1, 2, 4, 5]], fn d -> IntVariable.new(d) end)
model = Model.new(variables, [Constraint.new(AllDifferent, variables)])
{:ok, result} = CPSolver.solve(model)
assert Enum.sort(result.solutions) == Enum.sort(minizinc_solutions)
end
test "produces all possible permutations" do
var_nums = 4
domain = 1..var_nums
variables = Enum.map(domain, fn _ -> IntVariable.new(domain) end)
permutations = Permutation.permute!(Enum.to_list(domain))
model = Model.new(variables, [Constraint.new(AllDifferent, variables)])
{:ok, result} = CPSolver.solve(model)
assert result.statistics.solution_count == MapSet.size(permutations)
assert result.solutions |> MapSet.new() == permutations
end
test "unsatisfiable (duplicates)" do
variables = Enum.map(1..3, fn _ -> IntVariable.new(1) end)
assert catch_throw({:fail, _} = Model.new(variables, [Constraint.new(AllDifferent, variables)]))
end
test "unsatisfiable(pigeonhole)" do
variables = Enum.map(1..4, fn _ -> IntVariable.new(1..3) end)
assert catch_throw({:fail, _} = Model.new(variables, [Constraint.new(AllDifferent, variables)]))
end
test "views in variable list" do
n = 3
variables = Enum.map(1..n, fn i -> IntVariable.new(1..n, name: "row#{i}") end)
diagonal_down =
Enum.map(Enum.with_index(variables, 1), fn {var, idx} -> linear(var, 1, -idx) end)
diagonal_up =
Enum.map(Enum.with_index(variables, 1), fn {var, idx} -> linear(var, 1, idx) end)
model =
Model.new(
variables,
[
Constraint.new(AllDifferent, diagonal_down),
Constraint.new(AllDifferent, diagonal_up),
Constraint.new(AllDifferent, variables)
]
)
{:ok, res} = CPSolver.solve(model)
assert res.status == :unsatisfiable
end
end
end