diff --git a/Project.toml b/Project.toml
index b8a10506a2..7ac2d9ad9a 100644
--- a/Project.toml
+++ b/Project.toml
@@ -1,6 +1,6 @@
 name = "MathOptInterface"
 uuid = "b8f27783-ece8-5eb3-8dc8-9495eed66fee"
-version = "1.41.0"
+version = "1.42.0"
 
 [deps]
 BenchmarkTools = "6e4b80f9-dd63-53aa-95a3-0cdb28fa8baf"
diff --git a/docs/src/changelog.md b/docs/src/changelog.md
index b6c76c7c70..f3fa1a828d 100644
--- a/docs/src/changelog.md
+++ b/docs/src/changelog.md
@@ -7,6 +7,21 @@ CurrentModule = MathOptInterface
 The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
 and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
 
+## v1.42.0 (July 10, 2025)
+
+### Added
+
+ - Added an option to disable warnings in [`Utilities.PenaltyRelaxation`](@ref)
+   (#2774)
+
+### Fixed
+
+ - Fixed a bug writing objective constant in `MAX_SENSE` with `FileFormats.MPS`
+   (#2778)
+ - Fixed a change in how `==(::Expr, ::Expr)` works on for Julia nightly (#2780)
+ - Fixed a performance bug in the Hessian computation of `Nonlinear.ReverseAD`
+   (#2783)
+
 ## v1.41.0 (June 9, 2025)
 
 ### Added
diff --git a/src/FileFormats/MPS/MPS.jl b/src/FileFormats/MPS/MPS.jl
index 36f3e94d89..9d6de0173a 100644
--- a/src/FileFormats/MPS/MPS.jl
+++ b/src/FileFormats/MPS/MPS.jl
@@ -451,7 +451,7 @@ end
 function _extract_terms_objective(model, var_to_column, coefficients, flip_obj)
     obj_func = _get_objective(model)
     _extract_terms(var_to_column, coefficients, "OBJ", obj_func, flip_obj)
-    return obj_func.constant
+    return flip_obj ? -obj_func.constant : obj_func.constant
 end
 
 function _var_name(
diff --git a/src/Nonlinear/ReverseAD/forward_over_reverse.jl b/src/Nonlinear/ReverseAD/forward_over_reverse.jl
index 03ea1d89fc..c531fb9878 100644
--- a/src/Nonlinear/ReverseAD/forward_over_reverse.jl
+++ b/src/Nonlinear/ReverseAD/forward_over_reverse.jl
@@ -92,16 +92,19 @@ function _eval_hessian_chunk(
         for s in 1:chunk
             # If `chunk < chunk_size`, leaves junk in the unused components
             d.input_ϵ[(idx-1)*chunk_size+s] = ex.seed_matrix[r, offset+s-1]
+            # Ensure the output is clear in preparation for the chunk
+            d.output_ϵ[(idx-1)*chunk_size+s] = 0.0
         end
     end
     _hessian_slice_inner(d, ex, chunk_size)
-    fill!(d.input_ϵ, 0.0)
     # collect directional derivatives
     for r in eachindex(ex.rinfo.local_indices)
         @inbounds idx = ex.rinfo.local_indices[r]
         # load output_ϵ into ex.seed_matrix[r,k,k+1,...,k+remaining-1]
         for s in 1:chunk
             ex.seed_matrix[r, offset+s-1] = d.output_ϵ[(idx-1)*chunk_size+s]
+            # Reset the input in preparation for the next chunk
+            d.input_ϵ[(idx-1)*chunk_size+s] = 0.0
         end
     end
     return
@@ -122,7 +125,6 @@ end
 end
 
 function _hessian_slice_inner(d, ex, ::Type{T}) where {T}
-    fill!(d.output_ϵ, 0.0)
     output_ϵ = _reinterpret_unsafe(T, d.output_ϵ)
     subexpr_forward_values_ϵ =
         _reinterpret_unsafe(T, d.subexpression_forward_values_ϵ)
diff --git a/src/Test/test_nonlinear.jl b/src/Test/test_nonlinear.jl
index 1d746a3665..79829fbaf7 100644
--- a/src/Test/test_nonlinear.jl
+++ b/src/Test/test_nonlinear.jl
@@ -323,7 +323,7 @@ MOI.objective_expr(::FeasibilitySenseEvaluator) = :()
 
 function MOI.constraint_expr(::FeasibilitySenseEvaluator, i::Int)
     @assert i == 1
-    return :(x[$(MOI.VariableIndex(1))]^2 == 1)
+    return :(x[$(MOI.VariableIndex(1))]^2.0 == 1.0)
 end
 
 MOI.eval_objective(d::FeasibilitySenseEvaluator, x) = 0.0
@@ -1072,7 +1072,7 @@ written. External solvers can exclude this test without consequence.
 function test_nonlinear_Feasibility_internal(::MOI.ModelLike, ::Config)
     d = FeasibilitySenseEvaluator(true)
     @test MOI.objective_expr(d) == :()
-    @test MOI.constraint_expr(d, 1) == :(x[$(MOI.VariableIndex(1))]^2 == 1.0)
+    @test MOI.constraint_expr(d, 1) == :(x[$(MOI.VariableIndex(1))]^2.0 == 1.0)
     @test_throws AssertionError MOI.constraint_expr(d, 2)
     MOI.initialize(d, [:Grad, :Jac, :ExprGraph, :Hess])
     @test :Hess in MOI.features_available(d)
diff --git a/src/Utilities/penalty_relaxation.jl b/src/Utilities/penalty_relaxation.jl
index 3521cc3cce..ed414225fb 100644
--- a/src/Utilities/penalty_relaxation.jl
+++ b/src/Utilities/penalty_relaxation.jl
@@ -142,6 +142,7 @@ end
     PenaltyRelaxation(
         penalties = Dict{MOI.ConstraintIndex,Float64}();
         default::Union{Nothing,T} = 1.0,
+        warn::Bool = true,
     )
 
 A problem modifier that, when passed to [`MOI.modify`](@ref), destructively
@@ -187,6 +188,9 @@ cannot be modified in-place.
 
 To modify variable bounds, rewrite them as linear constraints.
 
+If a constraint cannot be modified, a warning is logged and the
+constraint is skipped. The warning can be disabled by setting `warn = false`.
+
 ## Example
 
 ```jldoctest
@@ -242,12 +246,14 @@ true
 mutable struct PenaltyRelaxation{T}
     default::Union{Nothing,T}
     penalties::Dict{MOI.ConstraintIndex,T}
+    warn::Bool
 
     function PenaltyRelaxation(
         p::Dict{MOI.ConstraintIndex,T};
         default::Union{Nothing,T} = one(T),
+        warn::Bool = true,
     ) where {T}
-        return new{T}(default, p)
+        return new{T}(default, p, warn)
     end
 end
 
@@ -286,7 +292,11 @@ function _modify_penalty_relaxation(
             map[ci] = MOI.modify(model, ci, ScalarPenaltyRelaxation(penalty))
         catch err
             if err isa MethodError && err.f == MOI.modify
-                @warn("Skipping PenaltyRelaxation for ConstraintIndex{$F,$S}")
+                if relax.warn
+                    @warn(
+                        "Skipping PenaltyRelaxation for ConstraintIndex{$F,$S}"
+                    )
+                end
                 return
             end
             rethrow(err)
diff --git a/test/FileFormats/MOF/MOF.jl b/test/FileFormats/MOF/MOF.jl
index 2e4297503b..5a58acb719 100644
--- a/test/FileFormats/MOF/MOF.jl
+++ b/test/FileFormats/MOF/MOF.jl
@@ -96,8 +96,8 @@ function HS071(x::Vector{MOI.VariableIndex})
         ExprEvaluator(
             :(x[$x1] * x[$x4] * (x[$x1] + x[$x2] + x[$x3]) + x[$x3]),
             [
-                :(x[$x1] * x[$x2] * x[$x3] * x[$x4] >= 25),
-                :(x[$x1]^2 + x[$x2]^2 + x[$x3]^2 + x[$x4]^2 == 40),
+                :(x[$x1] * x[$x2] * x[$x3] * x[$x4] >= 25.0),
+                :(x[$x1]^2.0 + x[$x2]^2.0 + x[$x3]^2.0 + x[$x4]^2.0 == 40.0),
             ],
         ),
         true,
@@ -117,7 +117,9 @@ function test_HS071()
     target = read(joinpath(@__DIR__, "nlp.mof.json"), String)
     target = replace(target, r"\s" => "")
     target = replace(target, "MathOptFormatModel" => "MathOptFormat Model")
-    @test read(TEST_MOF_FILE, String) == target
+    # Normalize .0 floats and integer representations in JSON
+    normalize(x) = replace(x, ".0" => "")
+    @test normalize(read(TEST_MOF_FILE, String)) == normalize(target)
     _validate(TEST_MOF_FILE)
     return
 end
@@ -308,7 +310,7 @@ function test_nonlinear_readingwriting()
     block = MOI.get(model2, MOI.NLPBlock())
     MOI.initialize(block.evaluator, [:ExprGraph])
     @test MOI.constraint_expr(block.evaluator, 1) ==
-          :(2 * x[$x] + sin(x[$x])^2 - x[$y] == 1.0)
+          :(2.0 * x[$x] + sin(x[$x])^2.0 - x[$y] == 1.0)
     _validate(TEST_MOF_FILE)
     return
 end
diff --git a/test/FileFormats/MPS/MPS.jl b/test/FileFormats/MPS/MPS.jl
index 8a642d3269..e9f770dba2 100644
--- a/test/FileFormats/MPS/MPS.jl
+++ b/test/FileFormats/MPS/MPS.jl
@@ -1610,6 +1610,57 @@ function test_int_round_trip()
     return
 end
 
+function test_obj_constant_min()
+    model = MOI.FileFormats.MPS.Model()
+    x = MOI.add_variable(model)
+    MOI.set(model, MOI.ObjectiveSense(), MOI.MIN_SENSE)
+    f = 1.0 * x + 2.0
+    MOI.set(model, MOI.ObjectiveFunction{typeof(f)}(), f)
+    io = IOBuffer()
+    write(io, model)
+    dest = MOI.FileFormats.MPS.Model()
+    seekstart(io)
+    read!(io, dest)
+    g = MOI.get(dest, MOI.ObjectiveFunction{typeof(f)}())
+    @test g.constant == 2.0
+    @test MOI.get(dest, MOI.ObjectiveSense()) == MOI.MIN_SENSE
+    return
+end
+
+function test_obj_constant_max_to_min()
+    model = MOI.FileFormats.MPS.Model()
+    x = MOI.add_variable(model)
+    MOI.set(model, MOI.ObjectiveSense(), MOI.MAX_SENSE)
+    f = 1.0 * x + 2.0
+    MOI.set(model, MOI.ObjectiveFunction{typeof(f)}(), f)
+    io = IOBuffer()
+    write(io, model)
+    dest = MOI.FileFormats.MPS.Model()
+    seekstart(io)
+    read!(io, dest)
+    g = MOI.get(dest, MOI.ObjectiveFunction{typeof(f)}())
+    @test g.constant == -2.0
+    @test MOI.get(dest, MOI.ObjectiveSense()) == MOI.MIN_SENSE
+    return
+end
+
+function test_obj_constant_max_to_max()
+    model = MOI.FileFormats.MPS.Model(; print_objsense = true)
+    x = MOI.add_variable(model)
+    MOI.set(model, MOI.ObjectiveSense(), MOI.MAX_SENSE)
+    f = 1.0 * x + 2.0
+    MOI.set(model, MOI.ObjectiveFunction{typeof(f)}(), f)
+    io = IOBuffer()
+    write(io, model)
+    dest = MOI.FileFormats.MPS.Model()
+    seekstart(io)
+    read!(io, dest)
+    g = MOI.get(dest, MOI.ObjectiveFunction{typeof(f)}())
+    @test g.constant == 2.0
+    @test MOI.get(dest, MOI.ObjectiveSense()) == MOI.MAX_SENSE
+    return
+end
+
 end  # TestMPS
 
 TestMPS.runtests()
diff --git a/test/FileFormats/NL/read.jl b/test/FileFormats/NL/read.jl
index 9c2b0a97a6..fcc0574b44 100644
--- a/test/FileFormats/NL/read.jl
+++ b/test/FileFormats/NL/read.jl
@@ -64,7 +64,8 @@ function test_parse_expr()
     # (* x1 (* 2 (* x4 x2)))
     seekstart(io)
     x = MOI.VariableIndex.(1:4)
-    @test NL._parse_expr(io, model) == :(*($(x[1]), *(2, *($(x[4]), $(x[2])))))
+    @test NL._parse_expr(io, model) ==
+          :(*($(x[1]), *(2.0, *($(x[4]), $(x[2])))))
     @test eof(io)
     return
 end
@@ -76,7 +77,7 @@ function test_parse_expr_nary()
     seekstart(io)
     x = MOI.VariableIndex.(1:4)
     @test NL._parse_expr(io, model) ==
-          :(+($(x[1])^2, $(x[3])^2, $(x[4])^2, $(x[2])^2))
+          :(+($(x[1])^2.0, $(x[3])^2.0, $(x[4])^2.0, $(x[2])^2.0))
     @test eof(io)
     return
 end
diff --git a/test/Nonlinear/Nonlinear.jl b/test/Nonlinear/Nonlinear.jl
index 4904585963..5c85b4b0b6 100644
--- a/test/Nonlinear/Nonlinear.jl
+++ b/test/Nonlinear/Nonlinear.jl
@@ -62,7 +62,7 @@ function test_parse_sin_squared()
     Nonlinear.set_objective(model, :(sin($x)^2))
     evaluator = Nonlinear.Evaluator(model)
     MOI.initialize(evaluator, [:ExprGraph])
-    @test MOI.objective_expr(evaluator) == :(sin(x[$x])^2)
+    @test MOI.objective_expr(evaluator) == :(sin(x[$x])^2.0)
     return
 end
 
@@ -72,7 +72,7 @@ function test_parse_ifelse()
     Nonlinear.set_objective(model, :(ifelse($x, 1, 2)))
     evaluator = Nonlinear.Evaluator(model)
     MOI.initialize(evaluator, [:ExprGraph])
-    @test MOI.objective_expr(evaluator) == :(ifelse(x[$x], 1, 2))
+    @test MOI.objective_expr(evaluator) == :(ifelse(x[$x], 1.0, 2.0))
     return
 end
 
@@ -83,7 +83,7 @@ function test_parse_ifelse_inequality_less()
     evaluator = Nonlinear.Evaluator(model)
     MOI.initialize(evaluator, [:ExprGraph])
     @test MOI.objective_expr(evaluator) ==
-          :(ifelse(x[$x] < 1, x[$x] - 1, x[$x] + 1))
+          :(ifelse(x[$x] < 1.0, x[$x] - 1.0, x[$x] + 1.0))
     return
 end
 
@@ -94,7 +94,7 @@ function test_parse_ifelse_inequality_greater()
     evaluator = Nonlinear.Evaluator(model)
     MOI.initialize(evaluator, [:ExprGraph])
     @test MOI.objective_expr(evaluator) ==
-          :(ifelse(x[$x] > 1, x[$x] - 1, x[$x] + 1))
+          :(ifelse(x[$x] > 1.0, x[$x] - 1.0, x[$x] + 1.0))
     return
 end
 
@@ -105,7 +105,7 @@ function test_parse_ifelse_comparison()
     evaluator = Nonlinear.Evaluator(model)
     MOI.initialize(evaluator, [:ExprGraph])
     @test MOI.objective_expr(evaluator) ==
-          :(ifelse(0 <= x[$x] <= 1, x[$x] - 1, x[$x] + 1))
+          :(ifelse(0.0 <= x[$x] <= 1.0, x[$x] - 1.0, x[$x] + 1.0))
     return
 end
 
@@ -251,7 +251,7 @@ function test_set_objective()
     @test model.objective == Nonlinear.parse_expression(model, input)
     evaluator = Nonlinear.Evaluator(model)
     MOI.initialize(evaluator, [:ExprGraph])
-    @test MOI.objective_expr(evaluator) == :(x[$x]^2 + 1)
+    @test MOI.objective_expr(evaluator) == :(x[$x]^2.0 + 1.0)
     return
 end
 
@@ -263,7 +263,7 @@ function test_set_objective_subexpression()
     Nonlinear.set_objective(model, :($expr^2))
     evaluator = Nonlinear.Evaluator(model)
     MOI.initialize(evaluator, [:ExprGraph])
-    @test MOI.objective_expr(evaluator) == :((x[$x]^2 + 1)^2)
+    @test MOI.objective_expr(evaluator) == :((x[$x]^2.0 + 1.0)^2.0)
     return
 end
 
@@ -276,7 +276,7 @@ function test_set_objective_nested_subexpression()
     Nonlinear.set_objective(model, :($expr_2^2))
     evaluator = Nonlinear.Evaluator(model)
     MOI.initialize(evaluator, [:ExprGraph])
-    @test MOI.objective_expr(evaluator) == :(((x[$x]^2 + 1)^2)^2)
+    @test MOI.objective_expr(evaluator) == :(((x[$x]^2.0 + 1.0)^2.0)^2.0)
     return
 end
 
@@ -287,7 +287,7 @@ function test_set_objective_parameter()
     Nonlinear.set_objective(model, :($x^2 + $p))
     evaluator = Nonlinear.Evaluator(model)
     MOI.initialize(evaluator, [:ExprGraph])
-    @test MOI.objective_expr(evaluator) == :(x[$x]^2 + 1.2)
+    @test MOI.objective_expr(evaluator) == :(x[$x]^2.0 + 1.2)
     return
 end
 
@@ -300,7 +300,7 @@ function test_add_constraint_less_than()
     @test model[c].set == set
     evaluator = Nonlinear.Evaluator(model)
     MOI.initialize(evaluator, [:ExprGraph])
-    @test MOI.constraint_expr(evaluator, 1) == :(x[$x]^2 + 1 <= 1.0)
+    @test MOI.constraint_expr(evaluator, 1) == :(x[$x]^2.0 + 1.0 <= 1.0)
     return
 end
 
@@ -311,7 +311,7 @@ function test_add_constraint_delete()
     _ = Nonlinear.add_constraint(model, :(sqrt($x)), MOI.LessThan(1.0))
     evaluator = Nonlinear.Evaluator(model)
     MOI.initialize(evaluator, [:ExprGraph])
-    @test MOI.constraint_expr(evaluator, 1) == :(x[$x]^2 + 1 <= 1.0)
+    @test MOI.constraint_expr(evaluator, 1) == :(x[$x]^2.0 + 1.0 <= 1.0)
     @test MOI.constraint_expr(evaluator, 2) == :(sqrt(x[$x]) <= 1.0)
     Nonlinear.delete(model, c1)
     evaluator = Nonlinear.Evaluator(model)
@@ -330,7 +330,7 @@ function test_add_constraint_greater_than()
     @test model[c].set == set
     evaluator = Nonlinear.Evaluator(model)
     MOI.initialize(evaluator, [:ExprGraph])
-    @test MOI.constraint_expr(evaluator, 1) == :(x[$x]^2 + 1 >= 1.0)
+    @test MOI.constraint_expr(evaluator, 1) == :(x[$x]^2.0 + 1.0 >= 1.0)
     return
 end
 
@@ -342,7 +342,7 @@ function test_add_constraint_equal_to()
     @test model[c].set == set
     evaluator = Nonlinear.Evaluator(model)
     MOI.initialize(evaluator, [:ExprGraph])
-    @test MOI.constraint_expr(evaluator, 1) == :(x[$x]^2 + 1 == 1.0)
+    @test MOI.constraint_expr(evaluator, 1) == :(x[$x]^2.0 + 1.0 == 1.0)
     return
 end
 
@@ -354,7 +354,7 @@ function test_add_constraint_interval()
     @test model[c].set == set
     evaluator = Nonlinear.Evaluator(model)
     MOI.initialize(evaluator, [:ExprGraph])
-    @test MOI.constraint_expr(evaluator, 1) == :(-1.0 <= x[$x]^2 + 1 <= 1.0)
+    @test MOI.constraint_expr(evaluator, 1) == :(-1.0 <= x[$x]^2.0 + 1.0 <= 1.0)
     return
 end
 
diff --git a/test/Utilities/penalty_relaxation.jl b/test/Utilities/penalty_relaxation.jl
index 226bf8a623..ae6c839f4b 100644
--- a/test/Utilities/penalty_relaxation.jl
+++ b/test/Utilities/penalty_relaxation.jl
@@ -65,6 +65,25 @@ function test_relax_bounds()
     return
 end
 
+function test_relax_no_warn()
+    input = """
+    variables: x, y
+    minobjective: x + y
+    x >= 0.0
+    y <= 0.0
+    x in ZeroOne()
+    y in Integer()
+    """
+    model = MOI.Utilities.Model{Float64}()
+    MOI.Utilities.loadfromstring!(model, input)
+    relaxation = MOI.Utilities.PenaltyRelaxation(; warn = false)
+    @test_logs MOI.modify(model, relaxation)
+    dest = MOI.Utilities.Model{Float64}()
+    MOI.Utilities.loadfromstring!(dest, input)
+    MOI.Bridges._test_structural_identical(model, dest)
+    return
+end
+
 function test_relax_affine_lessthan()
     _test_roundtrip(
         """