Add support for MOI.UserDefinedFunction

src/eago_optimizer/moi_wrapper.jl

@@ -314,4 +314,21 @@ function MOI.get(m::Optimizer, ::Type{VI}, name::String)
     else
         return index_storage
     end
-end
+end
+
+#####
+##### Support and set user-defined functions
+#####
+MOI.supports(m::Optimizer, ::MOI.UserDefinedFunction) = true
+
+function MOI.set(m::Optimizer, udf::MOI.UserDefinedFunction, f)
+    if isnothing(m._input_problem._nlp_data)
+        model = MOI.Nonlinear.Model()
+        backend = MOI.Nonlinear.SparseReverseMode()
+        vars = MOI.get(m, MOI.ListOfVariableIndices())
+        evaluator = MOI.Nonlinear.Evaluator(model, backend, vars) 
+        m._input_problem._nlp_data = MOI.NLPBlockData(evaluator)
+    end
+    MOI.Nonlinear.register_operator(m._input_problem._nlp_data.evaluator.model, udf.name, udf.arity, f...)
+    return nothing
+end

src/eago_optimizer/optimize/nonconvex/stack_management.jl

@@ -236,27 +236,26 @@ $(TYPEDSIGNATURES)
 Check the optimization problem for unbounded branching variables, which would interfere
 with EAGO's branch-and-bound routine since there are no well-defined branching rules
 for cases where the interval bounds contain `-Inf` or `Inf`. If any branching variables
-are missing bounds, add the missing bound at +/- 1E10 and warn the user.
+are missing bounds, add the missing bound at +/- 1E6 and warn the user.
 """
 function unbounded_check!(m::GlobalOptimizer)
     if m._parameters.unbounded_check
         unbounded_flag = false
         wp = m._working_problem
-        epigraph_flag = _variable_num(FullVar(), m) != m._input_problem._variable_count
-        for i = 1:_variable_num(BranchVar(), m) - epigraph_flag #Not including epigraph reformulation variable
+        for i = 1:_variable_num(BranchVar(), m)
             if !wp._variable_info[i].has_lower_bound
                 unbounded_flag = true
-                wp._variable_info[i] = VariableInfo(wp._variable_info[i], GT(-1E10))
+                wp._variable_info[i] = VariableInfo(wp._variable_info[i], GT(-1E6)) # Some solvers break if bounds are too large
             end
             if !wp._variable_info[i].has_upper_bound
                 unbounded_flag = true
-                wp._variable_info[i] = VariableInfo(wp._variable_info[i], LT(1E10))
+                wp._variable_info[i] = VariableInfo(wp._variable_info[i], LT(1E6)) # Some solvers break if bounds are too large
             end
         end
         unbounded_flag && @warn("""
         At least one branching variable is unbounded. This will interfere with EAGO's global
         optimization routine and may cause unexpected results. Bounds have been automatically
-        generated at +/- 1E10 for all unbounded variables, but tighter user-defined bounds are
+        generated at +/- 1E6 for all unbounded variables, but tighter user-defined bounds are
         highly recommended. To disable this warning and the automatic generation of bounds, use
         the option `unbounded_check = false`.""")
     end