Merge branch 'main' into rc_fixer_only_update_on_improvement

Pyomo · Nov 24, 2024 · d92b88d · d92b88d
2 parents c2d36df + 6681326
commit d92b88d
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Showing 3 changed files with 17 additions and 11 deletions.
diff --git a/doc/src/extensions.rst b/doc/src/extensions.rst
@@ -179,6 +179,9 @@ In its current state, the user might opt-in to presolve for two reasons:
 2. For problems where a "fixer" extension or spoke is used, determining tight bounds on the
    non-anticipative variables may improve the fixer's performance.
 
+.. Note::
+   Like many solvers, the presolver will convert infinite bounds to 1e+100.
+
 .. Note::
    This capability requires the auto-persistent pyomo solver interface (APPSI) extensions
    for Pyomo to be built on your system. This can be achieved by running ``pyomo build-extensions``

diff --git a/mpisppy/cylinders/reduced_costs_spoke.py b/mpisppy/cylinders/reduced_costs_spoke.py
@@ -145,22 +145,24 @@ def extract_and_store_reduced_costs(self):
 
                     # solver takes care of sign of rc, based on lb, ub and max,min
                     # rc can be of wrong sign if numerically 0 - accepted here, checked in extension
-                    if (xb - xvar.lb <= self.bound_tol) or (xvar.ub - xb <= self.bound_tol):
+                    if (xvar.lb is not None and xb - xvar.lb <= self.bound_tol) or (xvar.ub is not None and xvar.ub - xb <= self.bound_tol):
                         rc[ci] += sub._mpisppy_probability * sub.rc[xvar]
                     # not close to either bound -> rc = nan
                     else:
                         rc[ci] = np.nan
 
         self._scenario_rc_buffer.fill(0)
         ci = 0 # buffer index
-        for s in self.opt.local_scenarios.values():
-            for ndn_i, xvar in s._mpisppy_data.nonant_indices.items():
-                # fixed by modeler
-                if ndn_i in self._modeler_fixed_nonants[s]:
-                    self._scenario_rc_buffer[ci] = np.nan
-                else:
-                    self._scenario_rc_buffer[ci] = s.rc[xvar]
-                ci += 1
+        for sub in self.opt.local_subproblems.values():
+            for sn in sub.scen_list:
+                s = self.opt.local_scenarios[sn]
+                for ndn_i, xvar in s._mpisppy_data.nonant_indices.items():
+                    # fixed by modeler
+                    if ndn_i in self._modeler_fixed_nonants[s]:
+                        self._scenario_rc_buffer[ci] = np.nan
+                    else:
+                        self._scenario_rc_buffer[ci] = sub.rc[xvar]
+                    ci += 1
         self.rc_scenario = self._scenario_rc_buffer
         # print(f"In ReducedCostsSpoke; {self.rc_scenario=}")
 

diff --git a/mpisppy/opt/presolve.py b/mpisppy/opt/presolve.py
@@ -26,6 +26,7 @@
 
 from mpisppy import MPI
 
+_INF = 1e+100
 
 class _SPPresolver(abc.ABC):
     """Defines a presolver for distributed stochastic optimization problems
@@ -379,15 +380,15 @@ def _lb_generator(var_iterable):
     for v in var_iterable:
         lb = v.lb
         if lb is None:
-            yield -np.inf
+            yield -_INF
         yield lb
 
 
 def _ub_generator(var_iterable):
     for v in var_iterable:
         ub = v.ub
         if ub is None:
-            yield np.inf
+            yield _INF
         yield ub