Fix support for VectorOfVariables objectives

Project.toml

@@ -11,7 +11,7 @@ MathOptInterface = "b8f27783-ece8-5eb3-8dc8-9495eed66fee"
 Combinatorics = "1"
 HiGHS = "1"
 Ipopt = "1"
-MathOptInterface = "1.12"
+MathOptInterface = "1.13"
 julia = "1.6"
 
 [extras]

src/MultiObjectiveAlgorithms.jl

@@ -92,16 +92,6 @@ abstract type AbstractAlgorithm end
 
 MOI.Utilities.map_indices(::Function, x::AbstractAlgorithm) = x
 
-function _instantiate_with_cache(optimizer_factory)
-    model = MOI.instantiate(optimizer_factory)
-    if !MOI.supports_incremental_interface(model)
-        # A cache will already have been added
-        return model
-    end
-    cache = MOI.Utilities.UniversalFallback(MOI.Utilities.Model{Float64}())
-    return MOI.Utilities.CachingOptimizer(cache, model)
-end
-
 mutable struct Optimizer <: MOI.AbstractOptimizer
     inner::MOI.AbstractOptimizer
     algorithm::Union{Nothing,AbstractAlgorithm}
@@ -112,8 +102,13 @@ mutable struct Optimizer <: MOI.AbstractOptimizer
     solve_time::Float64
 
     function Optimizer(optimizer_factory)
+        inner = MOI.instantiate(
+            optimizer_factory;
+            with_bridge_type = Float64,
+            with_cache_type = Float64,
+        )
         return new(
-            _instantiate_with_cache(optimizer_factory),
+            inner,
             nothing,
             nothing,
             SolutionPoint[],

src/algorithms/Chalmet.jl

@@ -25,7 +25,8 @@ function _solve_constrained_model(
     rhs::Vector{Float64},
 )
     f = MOI.Utilities.scalarize(model.f)
-    MOI.set(model.inner, MOI.ObjectiveFunction{typeof(sum(f))}(), sum(f))
+    g = sum(1.0 * fi for fi in f)
+    MOI.set(model.inner, MOI.ObjectiveFunction{typeof(g)}(), g)
     constraints = [
         MOI.add_constraint(model.inner, f[1], MOI.LessThan(rhs[1] - 1))
         MOI.add_constraint(model.inner, f[2], MOI.LessThan(rhs[2] - 1))

src/algorithms/KirlikSayin.jl

@@ -172,7 +172,7 @@ function optimize_multiobjective!(algorithm::KirlikSayin, model::Optimizer)
         zₖ = MOI.get(model.inner, MOI.ObjectiveValue())
         # Solving the second stage model: Q_k(ε, zₖ)
         # Set objective sum(model.f)
-        sum_f = sum(scalars)
+        sum_f = sum(1.0 * s for s in scalars)
         MOI.set(model.inner, MOI.ObjectiveFunction{typeof(sum_f)}(), sum_f)
         # Constraint to eliminate weak dominance
         zₖ_constraint =

test/algorithms/Chalmet.jl

@@ -190,6 +190,21 @@ function test_infeasible()
     return
 end
 
+function test_vector_of_variables_objective()
+    model = MOA.Optimizer(HiGHS.Optimizer)
+    MOI.set(model, MOA.Algorithm(), MOA.Chalmet())
+    MOI.set(model, MOI.Silent(), true)
+    x = MOI.add_variables(model, 2)
+    MOI.add_constraint.(model, x, MOI.ZeroOne())
+    f = MOI.VectorOfVariables(x)
+    MOI.set(model, MOI.ObjectiveSense(), MOI.MIN_SENSE)
+    MOI.set(model, MOI.ObjectiveFunction{typeof(f)}(), f)
+    MOI.add_constraint(model, sum(1.0 * xi for xi in x), MOI.GreaterThan(1.0))
+    MOI.optimize!(model)
+    MOI.get(model, MOI.TerminationStatus()) == MOI.OPTIMAL
+    return
+end
+
 end
 
 TestChalmet.run_tests()

test/algorithms/Dichotomy.jl

@@ -392,6 +392,21 @@ function test_quadratic()
     return
 end
 
+function test_vector_of_variables_objective()
+    model = MOA.Optimizer(HiGHS.Optimizer)
+    MOI.set(model, MOA.Algorithm(), MOA.Dichotomy())
+    MOI.set(model, MOI.Silent(), true)
+    x = MOI.add_variables(model, 2)
+    MOI.add_constraint.(model, x, MOI.ZeroOne())
+    f = MOI.VectorOfVariables(x)
+    MOI.set(model, MOI.ObjectiveSense(), MOI.MIN_SENSE)
+    MOI.set(model, MOI.ObjectiveFunction{typeof(f)}(), f)
+    MOI.add_constraint(model, sum(1.0 * xi for xi in x), MOI.GreaterThan(1.0))
+    MOI.optimize!(model)
+    MOI.get(model, MOI.TerminationStatus()) == MOI.OPTIMAL
+    return
+end
+
 end
 
 TestDichotomy.run_tests()

test/algorithms/DominguezRios.jl

@@ -583,6 +583,21 @@ function test_time_limit()
     return
 end
 
+function test_vector_of_variables_objective()
+    model = MOA.Optimizer(HiGHS.Optimizer)
+    MOI.set(model, MOA.Algorithm(), MOA.DominguezRios())
+    MOI.set(model, MOI.Silent(), true)
+    x = MOI.add_variables(model, 2)
+    MOI.add_constraint.(model, x, MOI.ZeroOne())
+    f = MOI.VectorOfVariables(x)
+    MOI.set(model, MOI.ObjectiveSense(), MOI.MIN_SENSE)
+    MOI.set(model, MOI.ObjectiveFunction{typeof(f)}(), f)
+    MOI.add_constraint(model, sum(1.0 * xi for xi in x), MOI.GreaterThan(1.0))
+    MOI.optimize!(model)
+    MOI.get(model, MOI.TerminationStatus()) == MOI.OPTIMAL
+    return
+end
+
 end
 
 TestDominguezRios.run_tests()

test/algorithms/EpsilonConstraint.jl

@@ -417,6 +417,21 @@ function test_time_limit_large()
     return
 end
 
+function test_vector_of_variables_objective()
+    model = MOA.Optimizer(HiGHS.Optimizer)
+    MOI.set(model, MOA.Algorithm(), MOA.EpsilonConstraint())
+    MOI.set(model, MOI.Silent(), true)
+    x = MOI.add_variables(model, 2)
+    MOI.add_constraint.(model, x, MOI.ZeroOne())
+    f = MOI.VectorOfVariables(x)
+    MOI.set(model, MOI.ObjectiveSense(), MOI.MIN_SENSE)
+    MOI.set(model, MOI.ObjectiveFunction{typeof(f)}(), f)
+    MOI.add_constraint(model, sum(1.0 * xi for xi in x), MOI.GreaterThan(1.0))
+    MOI.optimize!(model)
+    MOI.get(model, MOI.TerminationStatus()) == MOI.OPTIMAL
+    return
+end
+
 end
 
 TestEpsilonConstraint.run_tests()

test/algorithms/Hierarchical.jl

@@ -107,6 +107,21 @@ function test_unbounded()
     return
 end
 
+function test_vector_of_variables_objective()
+    model = MOA.Optimizer(HiGHS.Optimizer)
+    MOI.set(model, MOA.Algorithm(), MOA.Hierarchical())
+    MOI.set(model, MOI.Silent(), true)
+    x = MOI.add_variables(model, 2)
+    MOI.add_constraint.(model, x, MOI.ZeroOne())
+    f = MOI.VectorOfVariables(x)
+    MOI.set(model, MOI.ObjectiveSense(), MOI.MIN_SENSE)
+    MOI.set(model, MOI.ObjectiveFunction{typeof(f)}(), f)
+    MOI.add_constraint(model, sum(1.0 * xi for xi in x), MOI.GreaterThan(1.0))
+    MOI.optimize!(model)
+    MOI.get(model, MOI.TerminationStatus()) == MOI.OPTIMAL
+    return
+end
+
 end
 
 TestHierarchical.run_tests()

test/algorithms/KirlikSayin.jl

@@ -586,6 +586,21 @@ function test_time_limit()
     return
 end
 
+function test_vector_of_variables_objective()
+    model = MOA.Optimizer(HiGHS.Optimizer)
+    MOI.set(model, MOA.Algorithm(), MOA.KirlikSayin())
+    MOI.set(model, MOI.Silent(), true)
+    x = MOI.add_variables(model, 2)
+    MOI.add_constraint.(model, x, MOI.ZeroOne())
+    f = MOI.VectorOfVariables(x)
+    MOI.set(model, MOI.ObjectiveSense(), MOI.MIN_SENSE)
+    MOI.set(model, MOI.ObjectiveFunction{typeof(f)}(), f)
+    MOI.add_constraint(model, sum(1.0 * xi for xi in x), MOI.GreaterThan(1.0))
+    MOI.optimize!(model)
+    MOI.get(model, MOI.TerminationStatus()) == MOI.OPTIMAL
+    return
+end
+
 end
 
 TestKirlikSayin.run_tests()

test/algorithms/Lexicographic.jl

@@ -150,6 +150,21 @@ function test_unbounded()
     return
 end
 
+function test_vector_of_variables_objective()
+    model = MOA.Optimizer(HiGHS.Optimizer)
+    MOI.set(model, MOA.Algorithm(), MOA.Lexicographic())
+    MOI.set(model, MOI.Silent(), true)
+    x = MOI.add_variables(model, 2)
+    MOI.add_constraint.(model, x, MOI.ZeroOne())
+    f = MOI.VectorOfVariables(x)
+    MOI.set(model, MOI.ObjectiveSense(), MOI.MIN_SENSE)
+    MOI.set(model, MOI.ObjectiveFunction{typeof(f)}(), f)
+    MOI.add_constraint(model, sum(1.0 * xi for xi in x), MOI.GreaterThan(1.0))
+    MOI.optimize!(model)
+    MOI.get(model, MOI.TerminationStatus()) == MOI.OPTIMAL
+    return
+end
+
 end
 
 TestLexicographic.run_tests()