Update missing future solver interfaces docs

doc/OnlineDocs/explanation/experimental/solvers.rst

@@ -51,6 +51,9 @@ with existing interfaces).
    * - Gurobi (direct)
      - ``gurobi_direct``
      - ``gurobi_direct_v2``
+   * - HiGHS
+     - ``highs``
+     - ``highs``
 
 Using the new interfaces through the legacy interface
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

doc/OnlineDocs/reference/topical/appsi/appsi.rst

@@ -24,17 +24,17 @@ example of using an APPSI solver interface.
 
 .. code-block:: python
 
-    >>> import pyomo.environ as pe
+    >>> import pyomo.environ as pyo
     >>> from pyomo.contrib import appsi
     >>> import numpy as np
     >>> from pyomo.common.timing import HierarchicalTimer
-    >>> m = pe.ConcreteModel()
-    >>> m.x = pe.Var()
-    >>> m.y = pe.Var()
-    >>> m.p = pe.Param(mutable=True)
-    >>> m.obj = pe.Objective(expr=m.x**2 + m.y**2)
-    >>> m.c1 = pe.Constraint(expr=m.y >= pe.exp(m.x))
-    >>> m.c2 = pe.Constraint(expr=m.y >= (m.x - m.p)**2)
+    >>> m = pyo.ConcreteModel()
+    >>> m.x = pyo.Var()
+    >>> m.y = pyo.Var()
+    >>> m.p = pyo.Param(mutable=True)
+    >>> m.obj = pyo.Objective(expr=m.x**2 + m.y**2)
+    >>> m.c1 = pyo.Constraint(expr=m.y >= pyo.exp(m.x))
+    >>> m.c2 = pyo.Constraint(expr=m.y >= (m.x - m.p)**2)
     >>> opt = appsi.solvers.Ipopt()
     >>> timer = HierarchicalTimer()
     >>> for p_val in np.linspace(1, 10, 100):
@@ -44,6 +44,15 @@ example of using an APPSI solver interface.
     >>>     print(res.best_feasible_objective)
     >>> print(timer)
 
+Alternatively, you can access the APPSI solvers through the classic
+``SolverFactory`` using the pattern ``appsi_solvername``.
+
+.. code-block:: python
+
+    >>> import pyomo.environ as pyo
+    >>> opt_ipopt = pyo.SolverFactory('appsi_ipopt')
+    >>> opt_highs = pyo.SolverFactory('appsi_highs')
+
 Extra performance improvements can be made if you know exactly what
 changes will be made in your model. In the example above, only
 parameter values are changed, so we can setup the