From 333e0a135b25ba3f75c58e076d6911e9bbcf0c88 Mon Sep 17 00:00:00 2001
From: Oscar Dowson <o.dowson@gmail.com>
Date: Wed, 18 Feb 2026 14:44:05 +1300
Subject: [PATCH 1/4] [breaking] remove ParameterValue and ParameterDual

---
 benchmark/run_benchmarks.jl      |  42 ++++------
 benchmark/run_benchmarks_jump.jl |  12 +--
 src/MOI_wrapper.jl               |  75 -----------------
 src/duals.jl                     |  64 ++++----------
 test/test_JuMP.jl                | 138 +++++++++++++++++--------------
 test/test_MathOptInterface.jl    |  27 +++---
 6 files changed, 129 insertions(+), 229 deletions(-)

diff --git a/benchmark/run_benchmarks.jl b/benchmark/run_benchmarks.jl
index f71a8a11..4caf25cc 100644
--- a/benchmark/run_benchmarks.jl
+++ b/benchmark/run_benchmarks.jl
@@ -94,9 +94,8 @@ function poi_add_saf_variables_and_parameters_ctr_parameter_update(
 )
     model = POI.Optimizer(MOI.Utilities.Model{Float64}())
     x = MOI.add_variables(model, N / 2)
-    y = first.(
-        MOI.add_constrained_variable.(model, MOI.Parameter.(ones(Int(N / 2)))),
-    )
+    p = MOI.add_constrained_variable.(model, MOI.Parameter.(ones(Int(N / 2))))
+    y, cy = first.(p), last.(p)
     for _ in 1:M
         MOI.add_constraint(
             model,
@@ -107,7 +106,7 @@ function poi_add_saf_variables_and_parameters_ctr_parameter_update(
             MOI.GreaterThan(1.0),
         )
     end
-    MOI.set.(model, POI.ParameterValue(), y, 0.5)
+    MOI.set.(model, MOI.ConstraintSet(), cy, MOI.Parameter(0.5))
     POI.update_parameters!(model)
     return
 end
@@ -169,9 +168,8 @@ end
 function poi_add_sqf_variables_parameters_ctr_parameter_update(N::Int, M::Int)
     model = POI.Optimizer(MOI.Utilities.Model{Float64}())
     x = MOI.add_variables(model, N / 2)
-    y = first.(
-        MOI.add_constrained_variable.(model, MOI.Parameter.(ones(Int(N / 2)))),
-    )
+    p = MOI.add_constrained_variable.(model, MOI.Parameter.(ones(Int(N / 2))))
+    y, cy = first.(p), last.(p)
     for _ in 1:M
         MOI.add_constraint(
             model,
@@ -183,7 +181,7 @@ function poi_add_sqf_variables_parameters_ctr_parameter_update(N::Int, M::Int)
             MOI.GreaterThan(1.0),
         )
     end
-    MOI.set.(model, POI.ParameterValue(), y, 0.5)
+    MOI.set.(model, MOI.ConstraintSet(), cy, MOI.Parameter(0.5))
     POI.update_parameters!(model)
     return
 end
@@ -211,9 +209,8 @@ end
 function poi_add_sqf_parameters_parameters_ctr_parameter_update(N::Int, M::Int)
     model = POI.Optimizer(MOI.Utilities.Model{Float64}())
     x = MOI.add_variables(model, N / 2)
-    y = first.(
-        MOI.add_constrained_variable.(model, MOI.Parameter.(ones(Int(N / 2)))),
-    )
+    p = MOI.add_constrained_variable.(model, MOI.Parameter.(ones(Int(N / 2))))
+    y, cy = first.(p), last.(p)
     for _ in 1:M
         MOI.add_constraint(
             model,
@@ -225,7 +222,7 @@ function poi_add_sqf_parameters_parameters_ctr_parameter_update(N::Int, M::Int)
             MOI.GreaterThan(1.0),
         )
     end
-    MOI.set.(model, POI.ParameterValue(), y, 0.5)
+    MOI.set.(model, MOI.ConstraintSet(), cy, MOI.Parameter(0.5))
     POI.update_parameters!(model)
     return
 end
@@ -281,9 +278,8 @@ function poi_add_saf_variables_and_parameters_obj_parameter_update(
 )
     model = POI.Optimizer(MOI.Utilities.Model{Float64}())
     x = MOI.add_variables(model, N / 2)
-    y = first.(
-        MOI.add_constrained_variable.(model, MOI.Parameter.(ones(Int(N / 2)))),
-    )
+    p = MOI.add_constrained_variable.(model, MOI.Parameter.(ones(Int(N / 2))))
+    y, cy = first.(p), last.(p)
     for _ in 1:M
         MOI.set(
             model,
@@ -295,7 +291,7 @@ function poi_add_saf_variables_and_parameters_obj_parameter_update(
         )
     end
     for _ in 1:M
-        MOI.set.(model, POI.ParameterValue(), y, 0.5)
+        MOI.set.(model, MOI.ConstraintSet(), cy, MOI.Parameter(0.5))
         POI.update_parameters!(model)
     end
     return
@@ -358,9 +354,8 @@ end
 function poi_add_sqf_variables_parameters_obj_parameter_update(N::Int, M::Int)
     model = POI.Optimizer(MOI.Utilities.Model{Float64}())
     x = MOI.add_variables(model, N / 2)
-    y = first.(
-        MOI.add_constrained_variable.(model, MOI.Parameter.(ones(Int(N / 2)))),
-    )
+    p = MOI.add_constrained_variable.(model, MOI.Parameter.(ones(Int(N / 2))))
+    y, cy = first.(p), last.(p)
     for _ in 1:M
         MOI.set(
             model,
@@ -373,7 +368,7 @@ function poi_add_sqf_variables_parameters_obj_parameter_update(N::Int, M::Int)
         )
     end
     for _ in 1:M
-        MOI.set.(model, POI.ParameterValue(), y, 0.5)
+        MOI.set.(model, MOI.ConstraintSet(), cy, MOI.Parameter(0.5))
         POI.update_parameters!(model)
     end
     return
@@ -402,9 +397,8 @@ end
 function poi_add_sqf_parameters_parameters_obj_parameter_update(N::Int, M::Int)
     model = POI.Optimizer(MOI.Utilities.Model{Float64}())
     x = MOI.add_variables(model, N / 2)
-    y = first.(
-        MOI.add_constrained_variable.(model, MOI.Parameter.(ones(Int(N / 2)))),
-    )
+    p = MOI.add_constrained_variable.(model, MOI.Parameter.(ones(Int(N / 2))))
+    y, cy = first.(p), last.(p)
     for _ in 1:M
         MOI.set(
             model,
@@ -417,7 +411,7 @@ function poi_add_sqf_parameters_parameters_obj_parameter_update(N::Int, M::Int)
         )
     end
     for _ in 1:M
-        MOI.set.(model, POI.ParameterValue(), y, 0.5)
+        MOI.set.(model, MOI.ConstraintSet(), cy, MOI.Parameter(0.5))
         POI.update_parameters!(model)
     end
     return
diff --git a/benchmark/run_benchmarks_jump.jl b/benchmark/run_benchmarks_jump.jl
index 6feb9d37..5449570e 100644
--- a/benchmark/run_benchmarks_jump.jl
+++ b/benchmark/run_benchmarks_jump.jl
@@ -131,7 +131,7 @@ function poi_add_saf_variables_and_parameters_ctr_parameter_update(
     @variable(model, x[i=1:Int(N/2)])
     @variable(model, p[i=1:Int(N/2)] in Parameter(0))
     @constraint(model, con[i=1:M], sum(x) + sum(p) >= 1)
-    MOI.set.(model, POI.ParameterValue(), p, 0.5)
+    set_parameter_value.(p, 0.5)
     POI.update_parameters!(backend(model))
     return
 end
@@ -189,7 +189,7 @@ function poi_add_sqf_variables_parameters_ctr_parameter_update(N::Int, M::Int)
     @variable(model, x[i=1:Int(N/2)])
     @variable(model, p[i=1:Int(N/2)] in Parameter(1))
     @constraint(model, con[i=1:M], x' * p >= 1)
-    MOI.set.(model, POI.ParameterValue(), p, 0.5)
+    set_parameter_value.(p, 0.5)
     POI.update_parameters!(backend(model))
     return
 end
@@ -221,7 +221,7 @@ function poi_add_sqf_parameters_parameters_ctr_parameter_update(N::Int, M::Int)
     @variable(model, x[i=1:Int(N/2)])
     @variable(model, p[i=1:Int(N/2)] in Parameter(1))
     @constraint(model, con[i=1:M], p' * p >= 1)
-    MOI.set.(model, POI.ParameterValue(), p, 0.5)
+    set_parameter_value.(p, 0.5)
     POI.update_parameters!(backend(model))
     return
 end
@@ -289,7 +289,7 @@ function poi_add_saf_variables_and_parameters_obj_parameter_update(
         @objective(model, Min, sum(x) + sum(p))
     end
     for _ in 1:M
-        MOI.set.(model, POI.ParameterValue(), p, 0.5)
+        set_parameter_value.(p, 0.5)
         POI.update_parameters!(backend(model))
     end
     return
@@ -357,7 +357,7 @@ function poi_add_sqf_variables_parameters_obj_parameter_update(N::Int, M::Int)
         @objective(model, Min, x' * p)
     end
     for _ in 1:M
-        MOI.set.(model, POI.ParameterValue(), p, 0.5)
+        set_parameter_value.(p, 0.5)
         POI.update_parameters!(backend(model))
     end
     return
@@ -395,7 +395,7 @@ function poi_add_sqf_parameters_parameters_obj_parameter_update(N::Int, M::Int)
         @objective(model, Min, p' * p)
     end
     for _ in 1:M
-        MOI.set.(model, POI.ParameterValue(), p, 0.5)
+        set_parameter_value.(p, 0.5)
         POI.update_parameters!(backend(model))
     end
     return
diff --git a/src/MOI_wrapper.jl b/src/MOI_wrapper.jl
index c1f5f0c0..0e605104 100644
--- a/src/MOI_wrapper.jl
+++ b/src/MOI_wrapper.jl
@@ -1816,81 +1816,6 @@ function MOI.get(model::Optimizer, ::ListOfParameterIndices)
     return collect(keys(model.parameters))::Vector{ParameterIndex}
 end
 
-"""
-    ParameterValue <: MOI.AbstractVariableAttribute
-
-Attribute defined to set and get parameter values
-
-# Example
-
-```julia
-MOI.set(model, POI.ParameterValue(), p, 2.0)
-MOI.get(model, POI.ParameterValue(), p)
-```
-"""
-struct ParameterValue <: MOI.AbstractVariableAttribute end
-
-# We need a CachingOptimizer fallback to
-# get ParameterValue working correctly on JuMP
-# TODO: Think of a better solution for this
-
-function MOI.set(
-    opt::MOI.Utilities.CachingOptimizer,
-    ::ParameterValue,
-    var::MOI.VariableIndex,
-    val::Float64,
-)
-    ci =
-        MOI.ConstraintIndex{MOI.VariableIndex,MOI.Parameter{Float64}}(var.value)
-    set = MOI.set(opt, MOI.ConstraintSet(), ci, MOI.Parameter(val))
-    return nothing
-end
-
-function MOI.set(
-    model::Optimizer,
-    ::ParameterValue,
-    var::MOI.VariableIndex,
-    val::Float64,
-)
-    ci =
-        MOI.ConstraintIndex{MOI.VariableIndex,MOI.Parameter{Float64}}(var.value)
-    set = MOI.set(model, MOI.ConstraintSet(), ci, MOI.Parameter(val))
-    return nothing
-end
-
-function MOI.set(
-    opt::MOI.Utilities.CachingOptimizer,
-    ::ParameterValue,
-    vi::MOI.VariableIndex,
-    val::Real,
-)
-    return MOI.set(opt, ParameterValue(), vi, convert(Float64, val))
-end
-
-function MOI.set(
-    model::Optimizer,
-    ::ParameterValue,
-    vi::MOI.VariableIndex,
-    val::Real,
-)
-    return MOI.set(model, ParameterValue(), vi, convert(Float64, val))
-end
-
-function MOI.get(
-    opt::MOI.Utilities.CachingOptimizer,
-    ::ParameterValue,
-    var::MOI.VariableIndex,
-)
-    ci =
-        MOI.ConstraintIndex{MOI.VariableIndex,MOI.Parameter{Float64}}(var.value)
-    set = MOI.get(opt, MOI.ConstraintSet(), ci)
-    return set.value
-end
-
-function MOI.get(model::Optimizer, ::ParameterValue, var::MOI.VariableIndex)
-    return model.parameters[p_idx(var)]
-end
-
 """
     ConstraintsInterpretation <: MOI.AbstractOptimizerAttribute
 
diff --git a/src/duals.jl b/src/duals.jl
index e488dbe7..7f6e593f 100644
--- a/src/duals.jl
+++ b/src/duals.jl
@@ -82,17 +82,14 @@ function _compute_parameters_in_ci!(
             cons_dual * term.coefficient
     end
     for term in pf.pp
-        coef = ifelse(term.variable_1 == term.variable_2, T(1 // 2), T(1))
+        mult = cons_dual * term.coefficient
+        if term.variable_1 == term.variable_2
+            mult /= 2
+        end
         model.dual_value_of_parameters[p_val(term.variable_1)] -=
-            coef *
-            cons_dual *
-            term.coefficient *
-            MOI.get(model, ParameterValue(), term.variable_2)
+            mult * model.parameters[p_idx(term.variable_2)]
         model.dual_value_of_parameters[p_val(term.variable_2)] -=
-            coef *
-            cons_dual *
-            term.coefficient *
-            MOI.get(model, ParameterValue(), term.variable_1)
+            mult * model.parameters[p_idx(term.variable_1)]
     end
     return
 end
@@ -119,30 +116,6 @@ function _update_duals_from_objective!(model::Optimizer{T}, pf) where {T}
     return
 end
 
-"""
-    ParameterDual <: MOI.AbstractVariableAttribute
-
-Attribute defined to get the dual values associated to parameters
-
-# Example
-
-```julia
-MOI.get(model, POI.ParameterValue(), p)
-```
-"""
-struct ParameterDual <: MOI.AbstractVariableAttribute end
-
-MOI.is_set_by_optimize(::ParametricOptInterface.ParameterDual) = true
-
-function MOI.get(
-    model::Optimizer{T},
-    ::ParameterDual,
-    v::MOI.VariableIndex,
-) where {T}
-    ci = MOI.ConstraintIndex{MOI.VariableIndex,MOI.Parameter{T}}(v.value)
-    return MOI.get(model, MOI.ConstraintDual(), ci)
-end
-
 function MOI.get(
     model::Optimizer{T},
     attr::MOI.ConstraintDual,
@@ -187,22 +160,15 @@ function _compute_parameters_in_ci!(
         model.dual_value_of_parameters[p_val(term.scalar_term.variable)] -=
             cons_dual[term.output_index] * term.scalar_term.coefficient
     end
-    for term in pf.pp
-        coef = ifelse(
-            term.scalar_term.variable_1 == term.scalar_term.variable_2,
-            T(1 // 2),
-            T(1),
-        )
-        model.dual_value_of_parameters[p_val(term.scalar_term.variable_1)] -=
-            coef *
-            cons_dual[term.output_index] *
-            term.scalar_term.coefficient *
-            MOI.get(model, ParameterValue(), term.scalar_term.variable_2)
-        model.dual_value_of_parameters[p_val(term.scalar_term.variable_2)] -=
-            coef *
-            cons_dual[term.output_index] *
-            term.scalar_term.coefficient *
-            MOI.get(model, ParameterValue(), term.scalar_term.variable_1)
+    for t in pf.pp
+        mult = cons_dual[t.output_index] * t.scalar_term.coefficient
+        if t.scalar_term.variable_1 == t.scalar_term.variable_2
+            mult /= 2
+        end
+        model.dual_value_of_parameters[p_val(t.scalar_term.variable_1)] -=
+            mult * model.parameters[p_idx(t.scalar_term.variable_2)]
+        model.dual_value_of_parameters[p_val(t.scalar_term.variable_2)] -=
+            mult * model.parameters[p_idx(t.scalar_term.variable_1)]
     end
     return
 end
diff --git a/test/test_JuMP.jl b/test/test_JuMP.jl
index 7a1e6c22..e4d04957 100644
--- a/test/test_JuMP.jl
+++ b/test/test_JuMP.jl
@@ -47,7 +47,7 @@ function test_jump_direct_affine_parameters()
     @test isapprox.(value(x[2]), 4.0 / 3.0, atol = ATOL)
     @test isapprox.(value(y), 0, atol = ATOL)
     # ===== Set parameter value =====
-    MOI.set(model, POI.ParameterValue(), y, 2.0)
+    set_parameter_value(y, 2.0)
     optimize!(model)
     @test isapprox.(value(x[1]), 0.0, atol = ATOL)
     @test isapprox.(value(x[2]), 2.0, atol = ATOL)
@@ -71,7 +71,7 @@ function test_jump_direct_parameter_times_variable()
     @test isapprox.(value(x[2]), 4.0 / 3.0, atol = ATOL)
     @test isapprox.(value(y), 0, atol = ATOL)
     # ===== Set parameter value =====
-    MOI.set(model, POI.ParameterValue(), y, 2.0)
+    set_parameter_value(y, 2.0)
     optimize!(model)
     @test isapprox.(value(x[1]), 0.0, atol = ATOL)
     @test isapprox.(value(x[2]), 2.0, atol = ATOL)
@@ -94,7 +94,7 @@ function test_jump_affine_parameters()
     @test isapprox.(value(x[2]), 4.0 / 3.0, atol = ATOL)
     @test isapprox.(value(y), 0, atol = ATOL)
     # ===== Set parameter value =====
-    MOI.set(model, POI.ParameterValue(), y, 2.0)
+    set_parameter_value(y, 2.0)
     optimize!(model)
     @test isapprox.(value(x[1]), 0.0, atol = ATOL)
     @test isapprox.(value(x[2]), 2.0, atol = ATOL)
@@ -109,7 +109,7 @@ function test_jump_parameter_times_variable()
     @variable(model, y in Parameter(0.0))
     @variable(model, w in Parameter(0.0))
     @variable(model, z in Parameter(0.0))
-    @test MOI.get(model, POI.ParameterValue(), y) == 0
+    @test parameter_value(y) == 0
     @constraint(model, 2 * x[1] + x[2] + y <= 4)
     @constraint(model, (1 + y) * x[1] + 2 * x[2] + z <= 4)
     @objective(model, Max, 4 * x[1] + 3 * x[2] + w)
@@ -118,7 +118,7 @@ function test_jump_parameter_times_variable()
     @test isapprox.(value(x[2]), 4.0 / 3.0, atol = ATOL)
     @test isapprox.(value(y), 0, atol = ATOL)
     # ===== Set parameter value =====
-    MOI.set(model, POI.ParameterValue(), y, 2.0)
+    set_parameter_value(y, 2.0)
     optimize!(model)
     @test isapprox.(value(x[1]), 0.0, atol = ATOL)
     @test isapprox.(value(x[2]), 2.0, atol = ATOL)
@@ -307,7 +307,7 @@ function test_jump_interpret_parameteric_bounds()
     @test Set(result) == Set(expected)
     @test length(result) == length(expected)
     @test objective_value(model) == -2
-    MOI.set(model, POI.ParameterValue(), p[1], 4.0)
+    set_parameter_value(p[1], 4.0)
     optimize!(model)
     @test objective_value(model) == 3
     return
@@ -337,7 +337,7 @@ function test_jump_interpret_parameteric_bounds_expression()
     @test Set(result) == Set(expected)
     @test length(result) == length(expected)
     @test objective_value(model) == -4
-    MOI.set(model, POI.ParameterValue(), p[1], 4.0)
+    set_parameter_value(p[1], 4.0)
     optimize!(model)
     @test objective_value(model) == 11.0
     return
@@ -365,7 +365,7 @@ function test_jump_direct_interpret_parameteric_bounds()
     @test Set(result) == Set(expected)
     @test length(result) == length(expected)
     @test objective_value(model) == -2
-    MOI.set(model, POI.ParameterValue(), p[1], 4.0)
+    set_parameter_value(p[1], 4.0)
     optimize!(model)
     @test objective_value(model) == 3
     return
@@ -396,7 +396,7 @@ function test_jump_direct_interpret_parameteric_bounds_no_interpretation()
     @test Set(result) == Set(expected)
     @test length(result) == length(expected)
     @test objective_value(model) == -2
-    MOI.set(model, POI.ParameterValue(), p[1], 4.0)
+    set_parameter_value(p[1], 4.0)
     optimize!(model)
     @test objective_value(model) == 3
     return
@@ -415,7 +415,7 @@ function test_jump_direct_interpret_parameteric_bounds_change()
     @objective(model, Min, sum(x))
     optimize!(model)
     @test objective_value(model) == -1
-    MOI.set(model, POI.ParameterValue(), p[1], 4.0)
+    set_parameter_value(p[1], 4.0)
     optimize!(model)
     @test objective_value(model) == 3.5
     return
@@ -432,7 +432,7 @@ function test_jump_direct_interpret_parameteric_bounds_both()
     @objective(model, Min, sum(x))
     optimize!(model)
     @test objective_value(model) == -1
-    MOI.set(model, POI.ParameterValue(), p[1], 4.0)
+    set_parameter_value(p[1], 4.0)
     optimize!(model)
     @test objective_value(model) == 3.5
     return
@@ -474,7 +474,7 @@ function test_jump_direct_get_parameter_value()
     @variable(model, z, set = MOI.Parameter(10.0))
     c = @constraint(model, 19.0 * x - z + 22.0 * y <= 1.0)
     @objective(model, Min, x + y)
-    @test MOI.get(model, POI.ParameterValue(), z) == 10
+    @test parameter_value(z) == 10
     return
 end
 
@@ -486,7 +486,7 @@ function test_jump_get_parameter_value()
     @variable(model, z, set = MOI.Parameter(10))
     c = @constraint(model, 19.0 * x - z + 22.0 * y <= 1.0)
     @objective(model, Min, x + y)
-    @test MOI.get(model, POI.ParameterValue(), z) == 10
+    @test parameter_value(z) == 10
     return
 end
 
@@ -499,7 +499,7 @@ function test_jump_sdp_scalar_parameter()
     @constraint(m, LinearAlgebra.Symmetric(x .- [1+p 0; 0 1+p]) in PSDCone())
     optimize!(m)
     @test all(isapprox.(value.(x), [1 0; 0 1], atol = ATOL))
-    MOI.set(m, POI.ParameterValue(), p, 1)
+    set_parameter_value(p, 1)
     optimize!(m)
     @test all(isapprox.(value.(x), [2 0; 0 2], atol = ATOL))
     return
@@ -516,7 +516,7 @@ function test_jump_sdp_matrix_parameter()
     optimize!(m)
     @test all(isapprox.(value.(x), P1, atol = ATOL))
     P2 = [1 2; 2 1]
-    MOI.set.(m, POI.ParameterValue(), p, P2)
+    set_parameter_value.(p, P2)
     optimize!(m)
     @test all(isapprox.(value.(x), P2, atol = ATOL))
     return
@@ -531,14 +531,14 @@ function test_jump_dual_basic()
     @objective(model, Min, 5 * y[1])
     optimize!(model)
     @test 5 / 3 ≈ dual(ctr1) atol = 1e-3
-    @test [-35 / 3, 0.0] ≈ MOI.get.(model, POI.ParameterDual(), x) atol = 1e-3
+    @test [-35 / 3, 0.0] ≈ dual.(ParameterRef.(x)) atol = 1e-3
     @test [-26 / 3, 0.0, 0.0, 0.0, 0.0, 0.0] ≈ value.(y) atol = 1e-3
     @test -130 / 3 ≈ objective_value(model) atol = 1e-3
     return
 end
 
 function test_jump_dual_multiplicative_fail()
-    model = Model(() -> POI.Optimizer(HiGHS.Optimizer))
+    model = direct_model(POI.Optimizer(HiGHS.Optimizer))
     set_silent(model)
     @variable(model, x)
     @variable(model, p in Parameter(1.0))
@@ -549,7 +549,19 @@ function test_jump_dual_multiplicative_fail()
         MOI.ConstraintDual(),
         "Cannot compute the dual of a multiplicative parameter",
     )
-    @test_throws err MOI.get(model, POI.ParameterDual(), p)
+    @test_throws err dual(ParameterRef(p))
+    return
+end
+
+function test_jump_dual_multiplicative_get_fallback()
+    model = Model(() -> POI.Optimizer(HiGHS.Optimizer))
+    set_silent(model)
+    @variable(model, x)
+    @variable(model, p in Parameter(1.0))
+    @constraint(model, cons, x * p >= 3)
+    @objective(model, Min, 2x)
+    optimize!(model)
+    @test isapprox(dual(ParameterRef(p)), -6; atol = 1e-4)
     return
 end
 
@@ -561,7 +573,7 @@ function test_jump_dual_objective_min()
     @constraint(model, cons, x >= 3 * p)
     @objective(model, Min, 2x + p)
     optimize!(model)
-    @test MOI.get(model, POI.ParameterDual(), p) == 7
+    @test dual(ParameterRef(p)) == 7
     return
 end
 
@@ -573,7 +585,7 @@ function test_jump_dual_objective_max()
     @constraint(model, cons, x >= 3 * p)
     @objective(model, Max, -2x + p)
     optimize!(model)
-    @test MOI.get(model, POI.ParameterDual(), p) == 5
+    @test dual(ParameterRef(p)) == 5
     return
 end
 
@@ -606,7 +618,7 @@ function test_jump_dual_multiple_parameters_1()
     @test 0.0 ≈ dual(ctr7) atol = 1e-3
     @test 0.0 ≈ dual(ctr8) atol = 1e-3
     @test [0.0, 0.0, -35 / 3, 0.0, 0.0, 0.0] ≈
-          MOI.get.(model, POI.ParameterDual(), x) atol = 1e-3
+          dual.(ParameterRef.(x)) atol = 1e-3
     @test [-26 / 3, 0.0, 0.0, 0.0, 0.0, 0.0] ≈ value.(y) atol = 1e-3
     @test -130 / 3 ≈ objective_value(model) atol = 1e-3
     return
@@ -622,13 +634,13 @@ function test_jump_duals_LessThan()
     optimize!(model)
     @test value(x) == -1.0
     @test dual(cref) == -1.0
-    @test MOI.get(model, POI.ParameterDual(), α) == -1.0
+    @test dual(ParameterRef(α)) == -1.0
 
-    MOI.set(model, POI.ParameterValue(), α, 2.0)
+    set_parameter_value(α, 2.0)
     optimize!(model)
     @test value(x) == 2.0
     @test dual(cref) == -1.0
-    @test MOI.get(model, POI.ParameterDual(), α) == -1.0
+    @test dual(ParameterRef(α)) == -1.0
     return
 end
 
@@ -642,12 +654,12 @@ function test_jump_duals_EqualTo()
     optimize!(model)
     @test value(x) == -1.0
     @test dual(cref) == -1.0
-    @test MOI.get(model, POI.ParameterDual(), α) == -1.0
-    MOI.set(model, POI.ParameterValue(), α, 2.0)
+    @test dual(ParameterRef(α)) == -1.0
+    set_parameter_value(α, 2.0)
     optimize!(model)
     @test value(x) == 2.0
     @test dual(cref) == -1.0
-    @test MOI.get(model, POI.ParameterDual(), α) == -1.0
+    @test dual(ParameterRef(α)) == -1.0
     return
 end
 
@@ -655,19 +667,19 @@ function test_jump_duals_GreaterThan()
     model = Model(() -> POI.Optimizer(HiGHS.Optimizer))
     set_silent(model)
     @variable(model, α in Parameter(1.0))
-    MOI.set(model, POI.ParameterValue(), α, -1.0)
+    set_parameter_value(α, -1.0)
     @variable(model, x)
     cref = @constraint(model, x >= α)
     @objective(model, Min, x)
     optimize!(model)
     @test value(x) == -1.0
     @test dual(cref) == 1.0
-    @test MOI.get(model, POI.ParameterDual(), α) == 1.0
-    MOI.set(model, POI.ParameterValue(), α, 2.0)
+    @test dual(ParameterRef(α)) == 1.0
+    set_parameter_value(α, 2.0)
     optimize!(model)
     @test value(x) == 2.0
     @test dual(cref) == 1.0
-    @test MOI.get(model, POI.ParameterDual(), α) == 1.0
+    @test dual(ParameterRef(α)) == 1.0
     return
 end
 
@@ -681,7 +693,7 @@ function test_jump_dual_multiple_parameters_2()
     optimize!(model)
     @test value(x) == 20.0
     @test dual(cref) == 1.0
-    @test MOI.get(model, POI.ParameterDual(), α[3]) == 2.0
+    @test dual(ParameterRef(α[3])) == 2.0
     return
 end
 
@@ -695,7 +707,7 @@ function test_jump_dual_mixing_params_and_vars_1()
     optimize!(model)
     @test value(x) == 2.0
     @test dual(cref) == 1 / 5
-    @test MOI.get(model, POI.ParameterDual(), α[3]) == 2 / 5
+    @test dual(ParameterRef(α[3])) == 2 / 5
     return
 end
 
@@ -709,7 +721,7 @@ function test_jump_dual_mixing_params_and_vars_2()
     optimize!(model)
     @test value(x) == 2.0
     @test dual(cref) == 1 / 5
-    @test MOI.get(model, POI.ParameterDual(), α[3]) == 2 / 5
+    @test dual(ParameterRef(α[3])) == 2 / 5
     return
 end
 
@@ -723,7 +735,7 @@ function test_jump_dual_mixing_params_and_vars_3()
     optimize!(model)
     @test value(x) == 4.0
     @test dual(cref) == 1 / 5
-    @test MOI.get(model, POI.ParameterDual(), α[3]) == 2 / 5
+    @test dual(ParameterRef(α[3])) == 2 / 5
     return
 end
 
@@ -731,21 +743,21 @@ function test_jump_dual_add_after_solve()
     model = Model(() -> POI.Optimizer(HiGHS.Optimizer))
     set_silent(model)
     @variable(model, α in Parameter(1.0))
-    MOI.set(model, POI.ParameterValue(), α, -1.0)
+    set_parameter_value(α, -1.0)
     @variable(model, x)
     cref = @constraint(model, x <= α)
     @objective(model, Max, x)
     optimize!(model)
     @test value(x) == -1.0
     @test dual(cref) == -1.0
-    @test MOI.get(model, POI.ParameterDual(), α) == -1.0
+    @test dual(ParameterRef(α)) == -1.0
     @variable(model, b in Parameter(-2.0))
     cref = @constraint(model, x <= b)
     optimize!(model)
     @test value(x) == -2.0
     @test dual(cref) == -1.0
-    @test MOI.get(model, POI.ParameterDual(), α) == 0.0
-    @test MOI.get(model, POI.ParameterDual(), b) == -1.0
+    @test dual(ParameterRef(α)) == 0.0
+    @test dual(ParameterRef(b)) == -1.0
     return
 end
 
@@ -760,7 +772,7 @@ function test_jump_dual_add_ctr_alaternative()
     optimize!(model)
     @test value(x) == -1.0
     @test dual(cref) == -1.0
-    @test MOI.get(model, POI.ParameterDual(), α) == -1.0
+    @test dual(ParameterRef(α)) == -1.0
     return
 end
 
@@ -778,12 +790,12 @@ function test_jump_dual_delete_constraint()
     @test value(x) == -1.0
     @test dual(cref1) == 0.0
     @test dual(cref2) == -1.0
-    @test MOI.get(model, POI.ParameterDual(), α) == -1.0
+    @test dual(ParameterRef(α)) == -1.0
     delete(model, cref2)
     optimize!(model)
     @test value(x) == -0.5
     @test dual(cref1) == -1.0
-    @test MOI.get(model, POI.ParameterDual(), α) == -0.5
+    @test dual(ParameterRef(α)) == -0.5
     return
 end
 
@@ -823,9 +835,9 @@ function test_jump_dual_delete_constraint_2()
         end
         @test dual(list[1]) == 1.0
         if i in [7, 4]
-            @test MOI.get(model, POI.ParameterDual(), α) == 0.0
+            @test dual(ParameterRef(α)) == 0.0
         else
-            @test MOI.get(model, POI.ParameterDual(), α) == 1.0 * i
+            @test dual(ParameterRef(α)) == 1.0 * i
         end
         con = popfirst!(list)
         delete(model, con)
@@ -872,9 +884,9 @@ function test_jump_dual_delete_constraint_3()
         end
         @test dual(list[1])[] ≈ 1.0 atol = 1e-5
         if i in [7, 4]
-            @test MOI.get(model, POI.ParameterDual(), α) ≈ 0.0 atol = 1e-5
+            @test dual(ParameterRef(α)) ≈ 0.0 atol = 1e-5
         else
-            @test MOI.get(model, POI.ParameterDual(), α) ≈ 1.0 * i atol = 1e-5
+            @test dual(ParameterRef(α)) ≈ 1.0 * i atol = 1e-5
         end
         con = popfirst!(list)
         delete(model, con)
@@ -914,7 +926,7 @@ function test_jump_direct_vector_parameter_affine_nonnegatives()
     optimize!(model)
     @test isapprox.(value(x), 4.0, atol = ATOL)
     @test isapprox.(value(y), 3.0, atol = ATOL)
-    MOI.set(model, POI.ParameterValue(), t, 6)
+    set_parameter_value(t, 6)
     optimize!(model)
     @test isapprox.(value(x), 5.0, atol = ATOL)
     @test isapprox.(value(y), 4.0, atol = ATOL)
@@ -942,7 +954,7 @@ function test_jump_direct_vector_parameter_affine_nonpositives()
     optimize!(model)
     @test isapprox.(value(x), 4.0, atol = ATOL)
     @test isapprox.(value(y), 3.0, atol = ATOL)
-    MOI.set(model, POI.ParameterValue(), t, 6)
+    set_parameter_value(t, 6)
     optimize!(model)
     @test isapprox.(value(x), 5.0, atol = ATOL)
     @test isapprox.(value(y), 4.0, atol = ATOL)
@@ -983,7 +995,7 @@ function test_jump_direct_soc_parameters()
     @test value(x) ≈ -1 / √2 atol = ATOL
     @test value(y) ≈ 1 / √2 atol = ATOL
     @test value(t) ≈ 1 atol = ATOL
-    MOI.set(model, POI.ParameterValue(), p, 1)
+    set_parameter_value(p, 1)
     optimize!(model)
     @test objective_value(model) ≈ 1 - 1 / √2 atol = ATOL
     @test value(x) ≈ 1 - 1 / √2 atol = ATOL
@@ -1020,7 +1032,7 @@ function test_jump_direct_rsoc_constraints()
     @test value(x) ≈ 1 / 4 atol = ATOL
     @test value(y) ≈ 1 / √2 atol = ATOL
     @test value(t) ≈ 1 atol = ATOL
-    MOI.set(model, POI.ParameterValue(), p, 2)
+    set_parameter_value(p, 2)
     optimize!(model)
     @test objective_value(model) ≈ 0.0 atol = ATOL
     @test value(x) ≈ 0.0 atol = ATOL
@@ -1040,11 +1052,11 @@ function test_jump_quadratic_interval()
     optimize!(model)
     @test value(x) ≈ 0 atol = ATOL
     @test value(y) ≈ 0.4 atol = ATOL
-    MOI.set(model, POI.ParameterValue(), p, 20.0)
+    set_parameter_value(p, 20.0)
     optimize!(model)
     @test value(x) ≈ 0 atol = ATOL
     @test value(y) ≈ 0.2 atol = ATOL
-    MOI.set(model, POI.ParameterValue(), q, 6.0)
+    set_parameter_value(q, 6.0)
     optimize!(model)
     @test value(x) ≈ 0 atol = ATOL
     @test value(y) ≈ 0.3 atol = ATOL
@@ -1068,11 +1080,11 @@ function test_jump_quadratic_interval_cached()
     optimize!(model)
     @test value(x) ≈ 0 atol = ATOL
     @test value(y) ≈ 0.4 atol = ATOL
-    MOI.set(model, POI.ParameterValue(), p, 20.0)
+    set_parameter_value(p, 20.0)
     optimize!(model)
     @test value(x) ≈ 0 atol = ATOL
     @test value(y) ≈ 0.2 atol = ATOL
-    MOI.set(model, POI.ParameterValue(), q, 6.0)
+    set_parameter_value(q, 6.0)
     optimize!(model)
     @test value(x) ≈ 0 atol = ATOL
     @test value(y) ≈ 0.3 atol = ATOL
@@ -1122,8 +1134,8 @@ function test_get_duals_from_multiplicative_parameters_1()
     @objective(model, Min, sum(x))
     optimize!(model)
     @test dual(c) ≈ 1.0 / 3.0
-    @test MOI.get.(model, POI.ParameterDual(), p1) ≈ 2.0 / 3
-    @test MOI.get.(model, POI.ParameterDual(), p2) ≈ 2.0 / 3
+    @test dual.(ParameterRef.(p1)) ≈ 2.0 / 3
+    @test dual.(ParameterRef.(p2)) ≈ 2.0 / 3
     return
 end
 
@@ -1137,8 +1149,8 @@ function test_get_duals_from_multiplicative_parameters_2()
     @objective(model, Min, sum(x))
     optimize!(model)
     @test dual(c) ≈ 1.0 / 3.0
-    @test MOI.get.(model, POI.ParameterDual(), p1) ≈ 2.0 / 3
-    @test MOI.get.(model, POI.ParameterDual(), p2) ≈ 40.0 / 3
+    @test dual.(ParameterRef.(p1)) ≈ 2.0 / 3
+    @test dual.(ParameterRef.(p2)) ≈ 40.0 / 3
     return
 end
 
@@ -1151,7 +1163,7 @@ function test_get_duals_from_multiplicative_parameters_3()
     @objective(model, Min, sum(x))
     optimize!(model)
     @test dual(c) ≈ 1.0 / 3.0
-    @test MOI.get.(model, POI.ParameterDual(), p) ≈ 2 * 4.0 / 3
+    @test dual.(ParameterRef.(p)) ≈ 2 * 4.0 / 3
     return
 end
 
@@ -1163,7 +1175,7 @@ function test_parameters_cannot_be_nan_1()
     @constraint(model, c, 3 * x >= p * p)
     @objective(model, Min, sum(x))
     @test_throws AssertionError optimize!(model)
-    MOI.set(model, POI.ParameterValue(), p, 20.0)
+    set_parameter_value(p, 20.0)
     return
 end
 
@@ -1176,7 +1188,7 @@ function test_parameters_cannot_be_nan_2()
     @variable(model, p in Parameter(1.0))
     @constraint(model, c, 3 * x[1] + x[2] >= p * p)
     @objective(model, Min, sum(x))
-    @test_throws AssertionError MOI.set(model, POI.ParameterValue(), p, NaN)
+    @test_throws AssertionError set_parameter_value(p, NaN)
     return
 end
 
@@ -1188,7 +1200,7 @@ function test_parameter_Cannot_be_inf_1()
     @constraint(model, c, 3 * x >= p * p)
     @objective(model, Min, sum(x))
     @test_throws AssertionError optimize!(model)
-    MOI.set(model, POI.ParameterValue(), p, 20.0)
+    set_parameter_value(p, 20.0)
     return
 end
 
@@ -1201,7 +1213,7 @@ function test_parameter_Cannot_be_inf_2()
     @variable(model, p in Parameter(1.0))
     @constraint(model, c, 3 * x[1] + x[2] >= p * p)
     @objective(model, Min, sum(x))
-    @test_throws AssertionError MOI.set(model, POI.ParameterValue(), p, Inf)
+    @test_throws AssertionError set_parameter_value(p, Inf)
     return
 end
 
diff --git a/test/test_MathOptInterface.jl b/test/test_MathOptInterface.jl
index 82fc5eae..dc1e2547 100644
--- a/test/test_MathOptInterface.jl
+++ b/test/test_MathOptInterface.jl
@@ -699,7 +699,7 @@ function test_vector_parameter_affine_nonnegatives()
     @test MOI.get(model, MOI.ObjectiveValue()) ≈ 7 atol = ATOL
     @test MOI.get(model, MOI.DualObjectiveValue()) ≈ 7 atol = ATOL
     @test MOI.get(model, MOI.ConstraintDual(), cnn) ≈ [1.0, 1.0] atol = ATOL
-    MOI.set(model, POI.ParameterValue(), t, 6)
+    MOI.set(model, MOI.ConstraintSet(), ct, MOI.Parameter(6.0))
     MOI.optimize!(model)
     @test MOI.get(model, MOI.VariablePrimal(), x) ≈ 5 atol = ATOL
     @test MOI.get(model, MOI.VariablePrimal(), y) ≈ 4 atol = ATOL
@@ -750,7 +750,7 @@ function test_vector_parameter_affine_nonpositives()
     @test MOI.get(model, MOI.ObjectiveValue()) ≈ 7 atol = ATOL
     @test MOI.get(model, MOI.DualObjectiveValue()) ≈ 7 atol = ATOL
     @test MOI.get(model, MOI.ConstraintDual(), cnn) ≈ [-1.0, -1.0] atol = ATOL
-    MOI.set(model, POI.ParameterValue(), t, 6)
+    MOI.set(model, MOI.ConstraintSet(), ct, MOI.Parameter(6.0))
     MOI.optimize!(model)
     @test MOI.get(model, MOI.VariablePrimal(), x) ≈ 5 atol = ATOL
     @test MOI.get(model, MOI.VariablePrimal(), y) ≈ 4 atol = ATOL
@@ -829,7 +829,7 @@ function test_vector_soc_parameters()
     @test MOI.get(model, MOI.VariablePrimal(), x) ≈ -1 / √2 atol = ATOL
     @test MOI.get(model, MOI.VariablePrimal(), y) ≈ 1 / √2 atol = ATOL
     @test MOI.get(model, MOI.VariablePrimal(), t) ≈ 1 atol = ATOL
-    MOI.set(model, POI.ParameterValue(), p, 1)
+    MOI.set(model, MOI.ConstraintSet(), cp, MOI.Parameter(1.0))
     MOI.optimize!(model)
     @test MOI.get(model, MOI.ObjectiveValue()) ≈ 1 - 1 / √2 atol = ATOL
     @test MOI.get(model, MOI.VariablePrimal(), x) ≈ 1 - 1 / √2 atol = ATOL
@@ -1459,13 +1459,16 @@ function test_qp_objective_parameter_times_parameter()
     MOI.set(optimizer, MOI.ConstraintSet(), cz, MOI.Parameter(3.0))
     MOI.optimize!(optimizer)
     @test isapprox(MOI.get(optimizer, MOI.ObjectiveValue()), 6.0, atol = ATOL)
-    MOI.set(optimizer, POI.ParameterValue(), y, 5)
-    MOI.set(optimizer, POI.ParameterValue(), z, 5.0)
-    @test_throws MOI.InvalidIndex MOI.set(
-        optimizer,
-        POI.ParameterValue(),
-        MOI.VariableIndex(10872368175),
-        5.0,
+    MOI.set(optimizer, MOI.ConstraintSet(), cy, MOI.Parameter(5.0))
+    MOI.set(optimizer, MOI.ConstraintSet(), cz, MOI.Parameter(5.0))
+    @test_throws(
+        MOI.InvalidIndex,
+        MOI.set(
+            optimizer,
+            MOI.ConstraintSet(),
+            typeof(cy)(cy.value + 10),
+            MOI.Parameter(5.0),
+        )
     )
     MOI.optimize!(optimizer)
     @test isapprox(MOI.get(optimizer, MOI.ObjectiveValue()), 25.0, atol = ATOL)
@@ -1994,7 +1997,7 @@ function test_psd_cone_with_parameter()
     model = POI.Optimizer(SCS.Optimizer; with_bridge_type = Float64)
     MOI.set(model, MOI.Silent(), true)
     x = MOI.add_variable(model)
-    p = first.(MOI.add_constrained_variable.(model, MOI.Parameter(1.0)))
+    p, cp = MOI.add_constrained_variable(model, MOI.Parameter(1.0))
 
     # Set objective: minimize x
     obj_func = MOI.ScalarAffineFunction([MOI.ScalarAffineTerm(1.0, x)], 0.0)
@@ -2018,7 +2021,7 @@ function test_psd_cone_with_parameter()
     @test MOI.get(model, MOI.TerminationStatus()) == MOI.OPTIMAL
     @test MOI.get(model, MOI.VariablePrimal(), x) ≈ 1.0 atol = 1e-5
 
-    MOI.set(model, POI.ParameterValue(), p, 3.0)
+    MOI.set(model, MOI.ConstraintSet(), cp, MOI.Parameter(3.0))
 
     MOI.optimize!(model)
     @test MOI.get(model, MOI.VariablePrimal(), x) ≈ 1 / 3 atol = 1e-5

From e481a75c4032ddb7fcacceee023e8f284d72b3a3 Mon Sep 17 00:00:00 2001
From: Oscar Dowson <o.dowson@gmail.com>
Date: Wed, 18 Feb 2026 15:03:26 +1300
Subject: [PATCH 2/4] Update

---
 test/test_JuMP.jl | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/test/test_JuMP.jl b/test/test_JuMP.jl
index e4d04957..4c9daf8c 100644
--- a/test/test_JuMP.jl
+++ b/test/test_JuMP.jl
@@ -617,8 +617,8 @@ function test_jump_dual_multiple_parameters_1()
           dual(ctr6) atol = 1e-3
     @test 0.0 ≈ dual(ctr7) atol = 1e-3
     @test 0.0 ≈ dual(ctr8) atol = 1e-3
-    @test [0.0, 0.0, -35 / 3, 0.0, 0.0, 0.0] ≈
-          dual.(ParameterRef.(x)) atol = 1e-3
+    @test [0.0, 0.0, -35 / 3, 0.0, 0.0, 0.0] ≈ dual.(ParameterRef.(x)) atol =
+        1e-3
     @test [-26 / 3, 0.0, 0.0, 0.0, 0.0, 0.0] ≈ value.(y) atol = 1e-3
     @test -130 / 3 ≈ objective_value(model) atol = 1e-3
     return

From 418e447eed9da02b1120d8b15b90b8ab849c9a17 Mon Sep 17 00:00:00 2001
From: Oscar Dowson <o.dowson@gmail.com>
Date: Wed, 18 Feb 2026 15:17:36 +1300
Subject: [PATCH 3/4] Update

---
 src/duals.jl      |  3 +--
 test/test_JuMP.jl | 19 +++----------------
 2 files changed, 4 insertions(+), 18 deletions(-)

diff --git a/src/duals.jl b/src/duals.jl
index 7f6e593f..3bf8af47 100644
--- a/src/duals.jl
+++ b/src/duals.jl
@@ -125,8 +125,7 @@ function MOI.get(
         msg = "$attr not available when evaluate_duals is set to false. Create an optimizer such as `POI.Optimizer(HiGHS.Optimizer; evaluate_duals = true)` to enable this feature."
         throw(MOI.GetAttributeNotAllowed(attr, msg))
     elseif !_is_additive(model, cp)
-        msg = "Cannot compute the dual of a multiplicative parameter"
-        throw(MOI.GetAttributeNotAllowed(attr, msg))
+        error("Cannot compute the dual of a multiplicative parameter")
     end
     return model.dual_value_of_parameters[p_val(cp)]
 end
diff --git a/test/test_JuMP.jl b/test/test_JuMP.jl
index 4c9daf8c..abfb182c 100644
--- a/test/test_JuMP.jl
+++ b/test/test_JuMP.jl
@@ -545,23 +545,10 @@ function test_jump_dual_multiplicative_fail()
     @constraint(model, cons, x * p >= 3)
     @objective(model, Min, 2x)
     optimize!(model)
-    err = MOI.GetAttributeNotAllowed(
-        MOI.ConstraintDual(),
-        "Cannot compute the dual of a multiplicative parameter",
+    @test_throws(
+        ErrorException("Cannot compute the dual of a multiplicative parameter"),
+        dual(ParameterRef(p)),
     )
-    @test_throws err dual(ParameterRef(p))
-    return
-end
-
-function test_jump_dual_multiplicative_get_fallback()
-    model = Model(() -> POI.Optimizer(HiGHS.Optimizer))
-    set_silent(model)
-    @variable(model, x)
-    @variable(model, p in Parameter(1.0))
-    @constraint(model, cons, x * p >= 3)
-    @objective(model, Min, 2x)
-    optimize!(model)
-    @test isapprox(dual(ParameterRef(p)), -6; atol = 1e-4)
     return
 end
 

From 993f0bab1b5e44c200e78ed1170c48df1f909f29 Mon Sep 17 00:00:00 2001
From: Oscar Dowson <o.dowson@gmail.com>
Date: Wed, 18 Feb 2026 15:47:28 +1300
Subject: [PATCH 4/4] Update

---
 test/test_MathOptInterface.jl | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/test/test_MathOptInterface.jl b/test/test_MathOptInterface.jl
index dc1e2547..e9e9ce65 100644
--- a/test/test_MathOptInterface.jl
+++ b/test/test_MathOptInterface.jl
@@ -2275,7 +2275,7 @@ function test_multiplicative_dual_error()
     f = 1.0 * x * p
     ci = MOI.add_constraint(model, f, MOI.EqualTo{Float64}(0.0))
     @test_throws(
-        MOI.GetAttributeNotAllowed,
+        ErrorException("Cannot compute the dual of a multiplicative parameter"),
         MOI.get(model, MOI.ConstraintDual(), pc),
     )
     return