Add support for interrupting during the solve loops

ext/MultiObjectiveAlgorithmsPolyhedraExt.jl

@@ -101,8 +101,9 @@ function MOA.minimize_multiobjective!(
     H = _halfspaces(IPS)
     count = 0
     while !isempty(H)
-        if MOA._time_limit_exceeded(model, start_time)
-            status = MOI.TIME_LIMIT
+        ret = MOA._check_premature_termination(model, start_time)
+        if ret !== nothing
+            status = ret
             break
         end
         count += 1

src/MultiObjectiveAlgorithms.jl

@@ -185,21 +185,6 @@ function MOI.set(model::Optimizer, ::MOI.TimeLimitSec, ::Nothing)
     return
 end
 
-function _time_limit_exceeded(model::Optimizer, start_time::Float64)
-    time_limit = MOI.get(model, MOI.TimeLimitSec())
-    if time_limit === nothing
-        return false
-    end
-    time_remaining = time_limit - (time() - start_time)
-    if time_remaining <= 0
-        return true
-    end
-    if MOI.supports(model.inner, MOI.TimeLimitSec())
-        MOI.set(model.inner, MOI.TimeLimitSec(), time_remaining)
-    end
-    return false
-end
-
 ### SolveTimeSec
 
 function MOI.get(model::Optimizer, ::MOI.SolveTimeSec)
@@ -604,7 +589,7 @@ end
 
 function _compute_ideal_point(model::Optimizer, start_time)
     for (i, f) in enumerate(MOI.Utilities.eachscalar(model.f))
-        if _time_limit_exceeded(model, start_time)
+        if _check_premature_termination(model, start_time) !== nothing
             return
         end
         if !isnan(model.ideal_point[i])
@@ -644,7 +629,39 @@ function optimize_multiobjective!(
     return minimize_multiobjective!(algorithm, model)
 end
 
+function _check_interrupt(f)
+    try
+        return reenable_sigint(f)
+    catch ex
+        if !(ex isa InterruptException)
+            rethrow(ex)
+        end
+        return MOI.INTERRUPTED
+    end
+end
+
+function _check_premature_termination(model::Optimizer, start_time::Float64)
+    return _check_interrupt() do
+        time_limit = MOI.get(model, MOI.TimeLimitSec())
+        if time_limit !== nothing
+            time_remaining = time_limit - (time() - start_time)
+            if time_remaining <= 0
+                return MOI.TIME_LIMIT
+            end
+            if MOI.supports(model.inner, MOI.TimeLimitSec())
+                MOI.set(model.inner, MOI.TimeLimitSec(), time_remaining)
+            end
+        end
+        return
+    end
+end
+
 function MOI.optimize!(model::Optimizer)
+    disable_sigint(() -> _optimize!(model))
+    return
+end
+
+function _optimize!(model::Optimizer)
     start_time = time()
     empty!(model.solutions)
     model.termination_status = MOI.OPTIMIZE_NOT_CALLED

src/algorithms/Chalmet.jl

@@ -101,8 +101,8 @@ function minimize_multiobjective!(algorithm::Chalmet, model::Optimizer)
     push!(Q, (1, 2))
     t = 3
     while !isempty(Q)
-        if _time_limit_exceeded(model, start_time)
-            return MOI.TIME_LIMIT, solutions
+        if (ret = _check_premature_termination(model, start_time)) !== nothing
+            return ret, solutions
         end
         r, s = pop!(Q)
         yr, ys = solutions[r].y, solutions[s].y

src/algorithms/Dichotomy.jl

@@ -77,16 +77,16 @@ function optimize_multiobjective!(algorithm::Dichotomy, model::Optimizer)
         error("Only scalar or bi-objective problems supported.")
     end
     if MOI.output_dimension(model.f) == 1
-        if _time_limit_exceeded(model, start_time)
-            return MOI.TIME_LIMIT, nothing
+        if (ret = _check_premature_termination(model, start_time)) !== nothing
+            return ret, nothing
         end
         status, solution = _solve_weighted_sum(model, algorithm, [1.0])
         return status, [solution]
     end
     solutions = Dict{Float64,SolutionPoint}()
     for (i, w) in (1 => 1.0, 2 => 0.0)
-        if _time_limit_exceeded(model, start_time)
-            return MOI.TIME_LIMIT, nothing
+        if (ret = _check_premature_termination(model, start_time)) !== nothing
+            return ret, nothing
         end
         status, solution = _solve_weighted_sum(model, algorithm, [w, 1.0 - w])
         if !_is_scalar_status_optimal(status)
@@ -103,8 +103,8 @@ function optimize_multiobjective!(algorithm::Dichotomy, model::Optimizer)
     limit = MOI.get(algorithm, SolutionLimit())
     status = MOI.OPTIMAL
     while length(queue) > 0 && length(solutions) < limit
-        if _time_limit_exceeded(model, start_time)
-            status = MOI.TIME_LIMIT
+        if (ret = _check_premature_termination(model, start_time)) !== nothing
+            status = ret
             break
         end
         (a, b) = popfirst!(queue)

src/algorithms/DominguezRios.jl

@@ -183,8 +183,8 @@ function minimize_multiobjective!(algorithm::DominguezRios, model::Optimizer)
     k = 0
     status = MOI.OPTIMAL
     while any(!isempty(l) for l in L)
-        if _time_limit_exceeded(model, start_time)
-            status = MOI.TIME_LIMIT
+        if (ret = _check_premature_termination(model, start_time)) !== nothing
+            status = ret
             break
         end
         i, k = _select_next_box(L, k)

src/algorithms/EpsilonConstraint.jl

@@ -111,8 +111,8 @@ function minimize_multiobjective!(
     bound -= constant
     status = MOI.OPTIMAL
     for _ in 3:n_points
-        if _time_limit_exceeded(model, start_time)
-            status = MOI.TIME_LIMIT
+        if (ret = _check_premature_termination(model, start_time)) !== nothing
+            status = ret
             break
         end
         MOI.set(model, MOI.ConstraintSet(), ci, MOI.LessThan{Float64}(bound))

src/algorithms/KirlikSayin.jl

@@ -117,8 +117,9 @@ function minimize_multiobjective!(algorithm::KirlikSayin, model::Optimizer)
     L = [_Rectangle(_project(yI, k), _project(yN, k))]
     status = MOI.OPTIMAL
     while !isempty(L)
-        if _time_limit_exceeded(model, start_time)
-            return MOI.TIME_LIMIT, solutions
+        if (ret = _check_premature_termination(model, start_time)) !== nothing
+            status = ret
+            break
         end
         max_volume_index = argmax([_volume(Rᵢ, _project(yI, k)) for Rᵢ in L])
         uᵢ = L[max_volume_index].u

src/algorithms/Lexicographic.jl

@@ -124,8 +124,8 @@ function _solve_in_sequence(
     solution = SolutionPoint[]
     status = MOI.OPTIMAL
     for i in sequence
-        if _time_limit_exceeded(model, start_time)
-            status = MOI.TIME_LIMIT
+        if (ret = _check_premature_termination(model, start_time)) !== nothing
+            status = ret
             break
         end
         f = scalars[i]

src/algorithms/RandomWeighting.jl

@@ -60,8 +60,9 @@ function optimize_multiobjective!(algorithm::RandomWeighting, model::Optimizer)
     #   * then the outer loop goes again
     while length(solutions) < MOI.get(algorithm, SolutionLimit())
         while length(solutions) < MOI.get(algorithm, SolutionLimit())
-            if _time_limit_exceeded(model, start_time)
-                return MOI.TIME_LIMIT, filter_nondominated(sense, solutions)
+            ret = _check_premature_termination(model, start_time)
+            if ret !== nothing
+                return ret, filter_nondominated(sense, solutions)
             end
             weights = rand(P)
             f = _scalarise(model.f, weights)

src/algorithms/TambyVanderpooten.jl

@@ -123,8 +123,8 @@ function minimize_multiobjective!(
     U_N[yN] = [[_get_child(yN, yI, k)] for k in 1:n]
     status = MOI.OPTIMAL
     while !isempty(U_N)
-        if _time_limit_exceeded(model, start_time)
-            status = MOI.TIME_LIMIT
+        if (ret = _check_premature_termination(model, start_time)) !== nothing
+            status = ret
             break
         end
         k, u = _select_search_zone(U_N, yI, yN)

test/test_model.jl

@@ -225,6 +225,15 @@ function test_SubproblemCount()
     return
 end
 
+function test_check_interrupt()
+    function _test_check_interrupt(err)
+        return disable_sigint(() -> MOA._check_interrupt(() -> throw(err)))
+    end
+    @test _test_check_interrupt(InterruptException()) == MOI.INTERRUPTED
+    @test_throws ArgumentError("") _test_check_interrupt(ArgumentError(""))
+    return
+end
+
 end  # module
 
 TestModel.run_tests()