Update DominguezRios to delete boxes that are already searched.

src/algorithms/DominguezRios.jl

@@ -190,13 +190,25 @@ function minimize_multiobjective!(algorithm::DominguezRios, model::Optimizer)
     solutions = SolutionPoint[]
     k = 0
     status = MOI.OPTIMAL
+    B_prevs = Vector{Union{Nothing,_DominguezRiosBox}}(nothing, n)
+    iter = 0
     while any(!isempty(l) for l in L)
+        iter += 1
         if (ret = _check_premature_termination(model)) !== nothing
             status = ret
             break
         end
         i, k = _select_next_box(L, k)
         B = L[k][i]
+        if iter > n
+            if !isnothing(B_prevs[k])
+                if (B_prevs[k].l ≈ B.l) && (B_prevs[k].u ≈ B.u)
+                    deleteat!(L[k], i)
+                    continue
+                end
+            end
+        end
+        B_prevs[k] = B
         # We're going to scale `w` here by `scale` instead of the usual
         # `1 / max(...)`. It will show up in a few places bbelow.
         w = scale ./ max.(1, B.u - yI)

test/algorithms/DominguezRios.jl

@@ -152,6 +152,25 @@ function test_vector_of_variables_objective()
     return
 end
 
+function test_lp()
+    model = MOI.instantiate(; with_bridge_type = Float64) do
+        return MOA.Optimizer(HiGHS.Optimizer)
+    end
+    MOI.set(model, MOA.Algorithm(), MOA.DominguezRios())
+    MOI.set(model, MOI.Silent(), true)
+    x = MOI.add_variables(model, 2)
+    MOI.add_constraint(model, x[1], MOI.GreaterThan(0.0))
+    MOI.add_constraint(model, x[2], MOI.Interval(0.0, 3.0))
+    MOI.add_constraint(model, 3.0 * x[1] - 1.0 * x[2], MOI.LessThan(6.0))
+    MOI.set(model, MOI.ObjectiveSense(), MOI.MIN_SENSE)
+    f = MOI.Utilities.vectorize([3.0 1.0; -1.0 -2.0] * x)
+    MOI.set(model, MOI.ObjectiveFunction{typeof(f)}(), f)
+    MOI.optimize!(model)
+    @test MOI.get(model, MOI.TerminationStatus()) == MOI.OPTIMAL
+    @test MOI.get(model, MOI.ResultCount()) > 1
+    return
+end
+
 end  # module TestDominguezRios
 
 TestDominguezRios.run_tests()