[Utilities] fix DualObjectiveValue fallback when DualStatus=NO_SOLUTION

src/Test/test_linear.jl

@@ -452,7 +452,11 @@ function setup_test(
             T[0, 0, 1],
             (MOI.ScalarAffineFunction{T}, MOI.LessThan{T}) => T[-2],
         ),
-        (mock::MOIU.MockOptimizer) -> MOIU.mock_optimize!(mock, T[-1, 0, 2]),
+        (mock::MOIU.MockOptimizer) -> MOIU.mock_optimize!(
+            mock,
+            T[-1, 0, 2],
+            (MOI.ScalarAffineFunction{T}, MOI.LessThan{T}) => T[-2],
+        ),
         (mock::MOIU.MockOptimizer) -> MOIU.mock_optimize!(mock, T[1, 0, 0]),
         (mock::MOIU.MockOptimizer) -> MOIU.mock_optimize!(mock, T[2, 0, 0]),
         (mock::MOIU.MockOptimizer) -> MOIU.mock_optimize!(mock, T[0, 2, 0]),

src/Utilities/results.jl

@@ -70,14 +70,18 @@ function get_fallback(
     ::Type{T},
 )::T where {T}
     MOI.check_result_index_bounds(model, attr)
+    status = MOI.get(model, MOI.DualStatus(attr.result_index))
+    if status == MOI.NO_SOLUTION
+        throw(MOI.GetAttributeNotAllowed(attr, "No dual solution is available"))
+    end
     value = zero(T) # sum will not work if there are zero constraints
     for (F, S) in MOI.get(model, MOI.ListOfConstraintTypesPresent())
         value += _dual_objective_value(model, F, S, T, attr.result_index)::T
     end
     if MOI.get(model, MOI.ObjectiveSense()) != MOI.MAX_SENSE
         value = -value
     end
-    if !is_ray(MOI.get(model, MOI.DualStatus()))
+    if !is_ray(status)
         # The objective constant should not be present in rays
         F = MOI.get(model, MOI.ObjectiveFunctionType())
         f = MOI.get(model, MOI.ObjectiveFunction{F}())

test/Utilities/test_mockoptimizer.jl

@@ -92,11 +92,12 @@ function test_optimizer_solve_with_result()
         ),
         MOI.get(optimizer, MOI.ObjectiveValue(2))
     )
+    MOI.set(optimizer, MOI.DualStatus(1), MOI.FEASIBLE_POINT)
     @test_throws(
         ErrorException(
             "No mock dual is set for constraint `$c1` at result index `1`.",
         ),
-        MOI.get(optimizer, MOI.DualObjectiveValue())
+        MOI.get(optimizer, MOI.DualObjectiveValue(1))
     )
     @test MOI.get(optimizer, MOI.DualObjectiveValue(2)) == 5.9
     @test MOI.get(optimizer, MOI.PrimalStatus()) == MOI.FEASIBLE_POINT

test/Utilities/test_results.jl

@@ -43,6 +43,7 @@ function _test_hyperrectangle(T)
     )
     MOI.set(model, MOI.ConstraintDual(), c1, T[4, -3])
     MOI.set(model, MOI.ConstraintDual(), c2, T[-2, 5])
+    MOI.set(model, MOI.DualStatus(), MOI.FEASIBLE_POINT)
     @test -53 == @inferred MOI.Utilities.get_fallback(
         model,
         MOI.DualObjectiveValue(),
@@ -93,6 +94,7 @@ function test_dual_objective_value_open_interval_Interval_variable_index()
     ]
         MOI.set(model, MOI.ObjectiveSense(), MOI.MIN_SENSE)
         MOI.set.(model, MOI.ConstraintDual(), c, dual)
+        MOI.set(model, MOI.DualStatus(), MOI.FEASIBLE_POINT)
         d = MOI.Utilities.get_fallback(model, MOI.DualObjectiveValue(), Float64)
         @test isapprox(d, obj)
         MOI.set.(model, MOI.ObjectiveSense(), MOI.MAX_SENSE)
@@ -142,6 +144,7 @@ function test_dual_objective_value_open_interval_Interval()
     ]
         MOI.set(model, MOI.ObjectiveSense(), MOI.MIN_SENSE)
         MOI.set.(model, MOI.ConstraintDual(), c, dual)
+        MOI.set(model, MOI.DualStatus(), MOI.FEASIBLE_POINT)
         d = MOI.Utilities.get_fallback(model, MOI.DualObjectiveValue(), Float64)
         @test isapprox(d, obj)
         MOI.set(model, MOI.ObjectiveSense(), MOI.MAX_SENSE)
@@ -193,6 +196,7 @@ function test_dual_objective_value_open_interval_Hyperrectangle_variable_index()
     ]
         MOI.set(model, MOI.ObjectiveSense(), MOI.MIN_SENSE)
         MOI.set(model, MOI.ConstraintDual(), c, dual)
+        MOI.set(model, MOI.DualStatus(), MOI.FEASIBLE_POINT)
         d = MOI.Utilities.get_fallback(model, MOI.DualObjectiveValue(), Float64)
         @test isapprox(d, obj)
         MOI.set(model, MOI.ObjectiveSense(), MOI.MAX_SENSE)
@@ -242,6 +246,7 @@ function test_dual_objective_value_open_interval_Hyperrectangle()
     ]
         MOI.set(model, MOI.ObjectiveSense(), MOI.MIN_SENSE)
         MOI.set(model, MOI.ConstraintDual(), c, dual)
+        MOI.set(model, MOI.DualStatus(), MOI.FEASIBLE_POINT)
         d = MOI.Utilities.get_fallback(model, MOI.DualObjectiveValue(), Float64)
         @test isapprox(d, obj)
         MOI.set(model, MOI.ObjectiveSense(), MOI.MAX_SENSE)
@@ -251,6 +256,41 @@ function test_dual_objective_value_open_interval_Hyperrectangle()
     return
 end
 
+function test_get_fallback_DualObjectiveValue()
+    T = Float64
+    model = MOI.Utilities.MockOptimizer(
+        MOI.Utilities.UniversalFallback(MOI.Utilities.Model{T}()),
+        T,
+    )
+    x = MOI.add_variables(model, 2)
+    c1 = MOI.add_constraint(
+        model,
+        MOI.VectorOfVariables(x),
+        MOI.HyperRectangle(T[3, -7], T[5, -2]),
+    )
+    c2 = MOI.add_constraint(
+        model,
+        MOI.Utilities.vectorize(x .+ T[11, 13]),
+        MOI.HyperRectangle(T[-T(6), -T(4)], [T(3), T(2)]),
+    )
+    attr = MOI.DualObjectiveValue()
+    @test_throws(
+        MOI.GetAttributeNotAllowed(attr, "No dual solution is available"),
+        MOI.Utilities.get_fallback(model, attr, T),
+    )
+    MOI.set(model, MOI.DualStatus(), MOI.FEASIBLE_POINT)
+    MOI.set(model, MOI.ConstraintDual(), c1, T[4, -3])
+    MOI.set(model, MOI.ConstraintDual(), c2, T[-2, 5])
+    @test MOI.Utilities.get_fallback(model, attr, T) == -53
+    MOI.set(model, MOI.ResultCount(), 2)
+    attr = MOI.DualObjectiveValue(2)
+    @test_throws(
+        MOI.GetAttributeNotAllowed(attr, "No dual solution is available"),
+        MOI.Utilities.get_fallback(model, attr, T),
+    )
+    return
+end
+
 end  # module TestResults
 
 TestResults.runtests()