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(
"""
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