Update code coverage

src/algorithms/KirlikSayin.jl

@@ -146,6 +146,8 @@ function minimize_multiobjective!(algorithm::KirlikSayin, model::Optimizer)
         end
         optimize_inner!(model)
         if !_is_scalar_status_optimal(model)
+            # If this fails, it likely means that the solver experienced a
+            # numerical error with this box. Just skip it.
             _remove_rectangle(L, _Rectangle(_project(yI, k), uᵢ))
             MOI.delete.(model, ε_constraints)
             continue
@@ -163,6 +165,8 @@ function minimize_multiobjective!(algorithm::KirlikSayin, model::Optimizer)
         )
         optimize_inner!(model)
         if !_is_scalar_status_optimal(model)
+            # If this fails, it likely means that the solver experienced a
+            # numerical error with this box. Just skip it.
             MOI.delete.(model, ε_constraints)
             MOI.delete(model, zₖ_constraint)
             _remove_rectangle(L, _Rectangle(_project(yI, k), uᵢ))

test/algorithms/Dichotomy.jl

@@ -440,6 +440,24 @@ function test_solve_failures()
     return
 end
 
+function test_scalar_time_limit()
+    model = MOA.Optimizer(HiGHS.Optimizer)
+    MOI.set(model, MOA.Algorithm(), MOA.Dichotomy())
+    MOI.set(model, MOI.Silent(), true)
+    MOI.set(model, MOI.TimeLimitSec(), 0.0)
+    MOI.Utilities.loadfromstring!(
+        model,
+        """
+        variables: x
+        minobjective: [2 * x]
+        x >= 0.0
+        """,
+    )
+    MOI.optimize!(model)
+    @test MOI.get(model, MOI.TerminationStatus()) == MOI.TIME_LIMIT
+    return
+end
+
 end  # module TestDichotomy
 
 TestDichotomy.run_tests()

test/algorithms/KirlikSayin.jl

@@ -11,6 +11,7 @@ import HiGHS
 import MultiObjectiveAlgorithms as MOA
 import MultiObjectiveAlgorithms: MOI
 
+include(joinpath(dirname(@__DIR__), "mock_optimizer.jl"))
 include(joinpath(dirname(@__DIR__), "problems.jl"))
 include(joinpath(dirname(@__DIR__), "vOptLib.jl"))
 
@@ -146,6 +147,36 @@ function test_vector_of_variables_objective()
     return
 end
 
+function test_solve_failures()
+    m, n = 2, 10
+    p1 = [5.0 1 10 8 3 5 3 3 7 2; 10 6 1 6 8 3 2 10 6 1]
+    p2 = [4.0 6 4 3 1 6 8 2 9 7; 8 8 8 2 4 8 8 1 10 1]
+    w = [5.0 9 3 5 10 5 7 10 7 8; 4 8 8 6 10 8 10 7 5 1]
+    b = [34.0, 33.0]
+    for fail_after in 0:5
+        model = MOA.Optimizer(mock_optimizer(fail_after))
+        MOI.set(model, MOA.Algorithm(), MOA.KirlikSayin())
+        x_ = MOI.add_variables(model, m * n)
+        x = reshape(x_, m, n)
+        MOI.add_constraint.(model, x, MOI.Interval(0.0, 1.0))
+        f = MOI.Utilities.operate(vcat, Float64, sum(p1 .* x), sum(p2 .* x))
+        MOI.set(model, MOI.ObjectiveSense(), MOI.MAX_SENSE)
+        MOI.set(model, MOI.ObjectiveFunction{typeof(f)}(), f)
+        for i in 1:m
+            f_i = sum(w[i, j] * x[i, j] for j in 1:n)
+            MOI.add_constraint(model, f_i, MOI.LessThan(b[i]))
+        end
+        for j in 1:n
+            MOI.add_constraint(model, sum(1.0 .* x[:, j]), MOI.EqualTo(1.0))
+        end
+        MOI.optimize!(model)
+        @test MOI.get(model, MOI.TerminationStatus()) ==
+             (fail_after <= 3 ? MOI.NUMERICAL_ERROR : MOI.OPTIMAL)
+        @test MOI.get(model, MOI.ResultCount()) == 0
+    end
+    return
+end
+
 end  # TestKirlikSayin
 
 TestKirlikSayin.run_tests()