address above comments

src/node_variables.jl

@@ -270,7 +270,7 @@ function JuMP.upper_bound(nvref::NodeVariableRef)
 end
 
 function JuMP.delete_upper_bound(nvref::NodeVariableRef)
-    JuMP.delete(JuMP.owner_model(nvref), JuMP.LowerBoundRef(nvref))
+    JuMP.delete(JuMP.owner_model(nvref), JuMP.UpperBoundRef(nvref))
     return nothing
 end
 

src/optigraph.jl

@@ -719,6 +719,15 @@ end
 # Objective function
 #
 
+function has_node_objective(graph::OptiGraph)
+    for node in all_nodes(graph)
+        if has_objective(node)
+            return true
+        end
+    end
+    return false
+end
+
 function set_to_node_objectives(graph::OptiGraph)
     obj = 0
     for node in all_nodes(graph)

src/optimizer_interface.jl

@@ -139,6 +139,15 @@ function JuMP.optimize!(
         throw(JuMP.NoOptimizer())
     end
 
+    # check for node objectives when graph objective is empty
+    if iszero(objective_function(graph))
+        if has_node_objective(graph)
+            @warn "The optigraph objective is empty but objectives exist on optinodes. 
+            If this is not intended, consider using `set_to_node_objectives(graph)` to 
+            set the graph objective function."
+        end
+    end
+
     try
         # make sure subgraph elements are tracked in parent graph after solve
         MOI.optimize!(graph_backend(graph))

src/optinode.jl

@@ -189,6 +189,20 @@ function JuMP.set_objective(
     return nothing
 end
 
+function JuMP.set_objective_function(node::OptiNode, func::JuMP.AbstractJuMPScalar)
+    # check that all func terms are for this node
+    unique(collect_nodes(func)) == [node] || error("Optinode does not own all variables.")
+    d = JuMP.object_dictionary(node)
+    d[(node, :objective_function)] = func
+    return nothing
+end
+
+function JuMP.set_objective_sense(node::OptiNode, sense::MOI.OptimizationSense)
+    d = JuMP.object_dictionary(node)
+    d[(node, :objective_sense)] = sense
+    return nothing
+end
+
 function JuMP.objective_function(node::OptiNode)
     return JuMP.object_dictionary(node)[(node, :objective_function)]
 end

test/test_optigraph.jl

@@ -160,6 +160,12 @@ function test_objective_functions()
     @test objective_function(graph) ==
         n1[:x] - n2[:x] + n3[:x][1]^2 + n3[:x][2]^2 + n4[:x]^2
 
+    JuMP.set_objective_function(n1, n1[:y])
+    JuMP.set_objective_sense(n1, MOI.MAX_SENSE)
+    set_to_node_objectives(graph)
+    @test objective_function(graph) ==
+        -n1[:y] - n2[:x] + n3[:x][1]^2 + n3[:x][2]^2 + n4[:x]^2
+
     @objective(n4, Min, n4[:x]^3)
     set_to_node_objectives(graph)
     @test typeof(objective_function(graph)) == GenericNonlinearExpr{NodeVariableRef}