From 9842ec46bd5f74046220a0b1020db0648ef5b805 Mon Sep 17 00:00:00 2001
From: Oscar Dowson <o.dowson@gmail.com>
Date: Wed, 4 Dec 2024 15:56:28 +1300
Subject: [PATCH 1/2] Fix dual objective value with free variable

---
 src/MOI_wrapper.jl  | 5 +++--
 test/MOI_wrapper.jl | 2 ++
 2 files changed, 5 insertions(+), 2 deletions(-)

diff --git a/src/MOI_wrapper.jl b/src/MOI_wrapper.jl
index 37310f1..17dd080 100644
--- a/src/MOI_wrapper.jl
+++ b/src/MOI_wrapper.jl
@@ -2271,9 +2271,10 @@ function _active_bound(l, x, u, d)
         end
     elseif isfinite(l)
         return l
-    else
-        @assert isfinite(u)
+    elseif isfinite(u)
         return u
+    else
+        return 0.0
     end
 end
 
diff --git a/test/MOI_wrapper.jl b/test/MOI_wrapper.jl
index 11b0482..f80a196 100644
--- a/test/MOI_wrapper.jl
+++ b/test/MOI_wrapper.jl
@@ -941,11 +941,13 @@ function test_active_bound()
         (0.0, 1.0, 1.0, -2.0) => 1.0,
         (0.0, 0.6, 1.0, -2.0) => 1.0,
         (0.0, 0.6, 1.0, 2.0) => 1.0,  # incorrect d but doesn't matter
+        (-Inf, 0.0, Inf, 0.0) => 0.0,
         # It's a ray. Choose based on sign
         (0.0, NaN, 1.0, 2.0) => 0.0,
         (0.0, NaN, 1.0, 1e-10) => 0.0,
         (0.0, NaN, 1.0, -2.0) => 1.0,
         (0.0, NaN, 1.0, -1e-10) => 1.0,
+        (-Inf, NaN, Inf, 0.0) => 0.0,
         # It's a one-sided ray
         (0.0, NaN, Inf, 2.0) => 0.0,
         (0.0, NaN, Inf, -1e-10) => 0.0,

From 9d3c9c02015f119c069c9cef6762600464d41f05 Mon Sep 17 00:00:00 2001
From: Oscar Dowson <o.dowson@gmail.com>
Date: Wed, 4 Dec 2024 16:40:01 +1300
Subject: [PATCH 2/2] Update

---
 test/MOI_wrapper.jl | 12 ++++++++++++
 1 file changed, 12 insertions(+)

diff --git a/test/MOI_wrapper.jl b/test/MOI_wrapper.jl
index f80a196..bd272ad 100644
--- a/test/MOI_wrapper.jl
+++ b/test/MOI_wrapper.jl
@@ -974,6 +974,18 @@ function test_add_constrained_variable_tuple()
     return
 end
 
+function test_dual_objective_value_infeasible()
+    model = HiGHS.Optimizer()
+    x = MOI.add_variable(model)
+    MOI.set(model, MOI.ObjectiveSense(), MOI.MIN_SENSE)
+    f = 1.0 * x
+    MOI.set(model, MOI.ObjectiveFunction{typeof(f)}(), f)
+    MOI.optimize!(model)
+    @test MOI.get(model, MOI.DualStatus()) == MOI.INFEASIBLE_POINT
+    @test MOI.get(model, MOI.DualObjectiveValue()) == 0.0
+    return
+end
+
 end  # module
 
 TestMOIHighs.runtests()