Update

Author: odow

src/algorithms/Chalmet.jl

@@ -41,6 +41,7 @@ function _solve_constrained_model(
 end
 
 function minimize_multiobjective!(algorithm::Chalmet, model::Optimizer)
+    @assert MOI.get(model.inner, MOI.ObjectiveSense()) == MOI.MIN_SENSE
     start_time = time()
     if MOI.output_dimension(model.f) != 2
         error("Chalmet requires exactly two objectives")

src/algorithms/DominguezRios.jl

@@ -143,8 +143,8 @@ function _update!(
 end
 
 function minimize_multiobjective!(algorithm::DominguezRios, model::Optimizer)
-    start_time = time()
     @assert MOI.get(model.inner, MOI.ObjectiveSense()) == MOI.MIN_SENSE
+    start_time = time()
     n = MOI.output_dimension(model.f)
     L = [_DominguezRiosBox[] for i in 1:n]
     scalars = MOI.Utilities.scalarize(model.f)

src/algorithms/EpsilonConstraint.jl

@@ -69,8 +69,8 @@ function minimize_multiobjective!(
     algorithm::EpsilonConstraint,
     model::Optimizer,
 )
-    start_time = time()
     @assert MOI.get(model.inner, MOI.ObjectiveSense()) == MOI.MIN_SENSE
+    start_time = time()
     if MOI.output_dimension(model.f) != 2
         error("EpsilonConstraint requires exactly two objectives")
     end

src/algorithms/KirlikSayin.jl

@@ -75,8 +75,8 @@ function _update_list(L::Vector{_Rectangle}, f::Vector{Float64})
 end
 
 function minimize_multiobjective!(algorithm::KirlikSayin, model::Optimizer)
-    start_time = time()
     @assert MOI.get(model.inner, MOI.ObjectiveSense()) == MOI.MIN_SENSE
+    start_time = time()
     solutions = SolutionPoint[]
     # Problem with p objectives.
     # Set k = 1, meaning the nondominated points will get projected

src/algorithms/TambyVanderpooten.jl

@@ -85,8 +85,8 @@ function minimize_multiobjective!(
     algorithm::TambyVanderpooten,
     model::Optimizer,
 )
-    start_time = time()
     @assert MOI.get(model.inner, MOI.ObjectiveSense()) == MOI.MIN_SENSE
+    start_time = time()
     warm_start_supported = false
     if MOI.supports(model, MOI.VariablePrimalStart(), MOI.VariableIndex)
         warm_start_supported = true

test/algorithms/Chalmet.jl

@@ -165,6 +165,23 @@ function test_unbounded()
     return
 end
 
+function test_invalid_feasibility()
+    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.GreaterThan(0.0))
+    MOI.add_constraint(model, 1.0 * x[1] + 1.0 * x[2], MOI.LessThan(-1.0))
+    MOI.set(model, MOI.ObjectiveSense(), MOI.FEASIBILITY_SENSE)
+    f = MOI.Utilities.operate(vcat, Float64, 1.0 .* x...)
+    MOI.set(model, MOI.ObjectiveFunction{typeof(f)}(), f)
+    MOI.optimize!(model)
+    @test MOI.get(model, MOI.TerminationStatus()) == MOI.INVALID_MODEL
+    @test MOI.get(model, MOI.PrimalStatus()) == MOI.NO_SOLUTION
+    @test MOI.get(model, MOI.DualStatus()) == MOI.NO_SOLUTION
+    return
+end
+
 function test_infeasible()
     model = MOA.Optimizer(HiGHS.Optimizer)
     MOI.set(model, MOA.Algorithm(), MOA.Chalmet())