Remove error from feasibility sense

src/objective_coefficients.jl

@@ -19,8 +19,10 @@ function set_dual_model_sense(
         MOI.MAX_SENSE
     elseif primal_sense == MOI.MAX_SENSE
         MOI.MIN_SENSE
-    else # primal_sense == MOI.FEASIBILITY_SENSE
-        error(primal_sense, " is not supported")
+    elseif primal_sense == MOI.FEASIBILITY_SENSE 
+        # We assume fesibility sense is a Min 0
+        # so the dual would be Max ...
+        MOI.MAX_SENSE
     end
     MOI.set(dual_model, MOI.ObjectiveSense(), dual_sense)
     return

test/Problems/Feasibility/feasibility_problems.jl

@@ -0,0 +1,21 @@
+function feasibility_1_test()
+    #=
+        min 0
+    s.t.
+        x_1 + 2x_2 <= 3
+        x_1 >= 3
+    =#
+    model = TestModel{Float64}()
+
+    X = MOI.add_variables(model, 2)
+
+    MOI.add_constraint(
+        model,
+        MOI.ScalarAffineFunction(MOI.ScalarAffineTerm.([1.0, 2.0], X), 0.0),
+        MOI.LessThan(3.0),
+    )
+
+    MOI.add_constraint(model, X[1], MOI.GreaterThan(3.0))
+
+    return model
+end

test/Tests/test_dualize_feasibility.jl

@@ -0,0 +1,53 @@
+@testset "linear problems" begin
+    @testset "feasibility_1_test" begin
+        #=
+        primal
+            min 0
+        s.t.
+            x_1 >= 3         :y_2
+            x_1 + 2x_2 <= 3  :y_3
+        dual
+            max 3y_2 + 3y_3
+        s.t.
+            y_2 >= 0
+            y_3 <= 0
+            y_2 + y_3 == 0    :x_1
+            2y_3 == 0        :x_2
+        =#
+        primal_model = feasibility_1_test()
+        dual_model, primal_dual_map = dual_model_and_map(primal_model)
+
+        @test MOI.get(dual_model, MOI.NumberOfVariables()) == 2
+        list_of_cons = MOI.get(dual_model, MOI.ListOfConstraintTypesPresent())
+        @test Set(list_of_cons) == Set(
+            [
+                (MOI.VariableIndex, MOI.GreaterThan{Float64})
+                (MOI.VariableIndex, MOI.LessThan{Float64})
+                (MOI.ScalarAffineFunction{Float64}, MOI.EqualTo{Float64})
+            ],
+        )
+        @test MOI.get(
+            dual_model,
+            MOI.NumberOfConstraints{
+                MOI.VariableIndex,
+                MOI.GreaterThan{Float64},
+            }(),
+        ) == 1
+        @test MOI.get(
+            dual_model,
+            MOI.NumberOfConstraints{MOI.VariableIndex,MOI.LessThan{Float64}}(),
+        ) == 1
+        @test MOI.get(
+            dual_model,
+            MOI.NumberOfConstraints{
+                MOI.ScalarAffineFunction{Float64},
+                MOI.EqualTo{Float64},
+            }(),
+        ) == 2
+        obj_type = MOI.get(dual_model, MOI.ObjectiveFunctionType())
+        @test obj_type == MOI.ScalarAffineFunction{Float64}
+        obj = MOI.get(dual_model, MOI.ObjectiveFunction{obj_type}())
+        @test MOI.constant(obj) == 0.0
+        @test MOI.coefficient.(obj.terms) == [3.0; 3.0]
+    end
+end

test/runtests.jl

@@ -54,6 +54,7 @@ include("Problems/RSOC/rsoc_problems.jl")
 include("Problems/SDP/sdp_triangle_problems.jl")
 include("Problems/Exponential/exponential_cone_problems.jl")
 include("Problems/Power/power_cone_problems.jl")
+include("Problems/Feasibility/feasibility_problems.jl")
 
 # Run tests to travis ci
 include("Tests/test_structures.jl")
@@ -63,6 +64,7 @@ include("Tests/test_dual_model_variables.jl")
 include("Tests/test_dual_sets.jl")
 include("Tests/test_dualize_conic_linear.jl")
 include("Tests/test_dualize_linear.jl")
+include("Tests/test_dualize_feasibility.jl")
 include("Tests/test_dualize_soc.jl")
 include("Tests/test_dualize_rsoc.jl")
 include("Tests/test_dualize_sdp.jl")