Updates to Solution Pool

pyomo/contrib/alternative_solutions/aos_utils.py

@@ -306,8 +306,9 @@ def get_model_variables(
 
 
 class MyMunch(Munch):
-
-    to_dict = Munch.toDict
+    #WEH, MPV needed to add a to_dict since Bunch did not have one
+    def to_dict(self):
+        return _to_dict(self)
 
 
 def _to_dict(x):
@@ -319,4 +320,5 @@ def _to_dict(x):
     elif xtype in [dict, Munch, MyMunch]:
         return {k: _to_dict(v) for k, v in x.items()}
     else:
+        print(f'Here: {x=} {type(x)}')
         return x.to_dict()

pyomo/contrib/alternative_solutions/balas.py

@@ -45,7 +45,7 @@ def enumerate_binary_solutions(
     model : ConcreteModel
         A concrete Pyomo model
     num_solutions : int
-        The maximum number of solutions to generate.
+        The maximum number of solutions to generate. Must be positive
     variables: None or a collection of Pyomo _GeneralVarData variables
         The variables for which bounds will be generated. None indicates
         that all variables will be included. Alternatively, a collection of
@@ -83,6 +83,10 @@ def enumerate_binary_solutions(
     """
     logger.info("STARTING NO-GOOD CUT ANALYSIS")
 
+    assert num_solutions >= 1, "num_solutions must be positive integer"
+    if num_solutions == 1:
+        logger.warning("Running alternative_solutions method to find only 1 solution!")
+
     assert search_mode in [
         "optimal",
         "random",

pyomo/contrib/alternative_solutions/gurobi_solnpool.py

@@ -30,6 +30,7 @@ def gurobi_generate_solutions(
     solver_options={},
     tee=False,
     poolmanager=None,
+    pool_search_mode=2,
 ):
     """
     Finds alternative optimal solutions for discrete variables using Gurobi's
@@ -42,7 +43,7 @@ def gurobi_generate_solutions(
         A concrete Pyomo model.
     num_solutions : int
         The maximum number of solutions to generate. This parameter maps to
-        the PoolSolutions parameter in Gurobi.
+        the PoolSolutions parameter in Gurobi. Must be positive.
     rel_opt_gap : non-negative float or None
         The relative optimality gap for allowable alternative solutions.
         None implies that there is no limit on the relative optimality gap
@@ -59,12 +60,27 @@ def gurobi_generate_solutions(
         Boolean indicating that the solver output should be displayed.
     poolmanager : None
         Optional pool manager that will be used to collect solution
+    pool_search_mode : 1 or 2
+        The generation method for filling the pool.
+        This parameter maps to the PoolSearchMode in gurobi.
+        Method designed to work with value 2 as optimality ordered.
 
     Returns
     -------
     poolmanager
         A PyomoPoolManager object
     """
+
+    assert num_solutions >= 1, "num_solutions must be positive integer"
+    if num_solutions == 1:
+        logger.warning("Running alternative_solutions method to find only 1 solution!")
+
+    assert pool_search_mode in [1, 2], "pool_search_mode must be 1 or 2"
+    if pool_search_mode == 1:
+        logger.warning(
+            "Running gurobi_solnpool with PoolSearchMode=1, best effort search may lead to unexpected behavior"
+        )
+
     if poolmanager is None:
         poolmanager = PyomoPoolManager()
         poolmanager.add_pool("gurobi_generate_solutions", policy="keep_all")
@@ -78,7 +94,7 @@ def gurobi_generate_solutions(
     opt.config.stream_solver = tee
     opt.config.load_solution = False
     opt.gurobi_options["PoolSolutions"] = num_solutions
-    opt.gurobi_options["PoolSearchMode"] = 2
+    opt.gurobi_options["PoolSearchMode"] = pool_search_mode
     if rel_opt_gap is not None:
         opt.gurobi_options["PoolGap"] = rel_opt_gap
     if abs_opt_gap is not None:

pyomo/contrib/alternative_solutions/lp_enum.py

@@ -47,7 +47,7 @@ def enumerate_linear_solutions(
     model : ConcreteModel
         A concrete Pyomo model
     num_solutions : int
-        The maximum number of solutions to generate.
+        The maximum number of solutions to generate. Must be positive
     rel_opt_gap : float or None
         The relative optimality gap for the original objective for which
         variable bounds will be found. None indicates that a relative gap
@@ -83,6 +83,10 @@ def enumerate_linear_solutions(
     """
     logger.info("STARTING LP ENUMERATION ANALYSIS")
 
+    assert num_solutions >= 1, "num_solutions must be positive integer"
+    if num_solutions == 1:
+        logger.warning("Running alternative_solutions method to find only 1 solution!")
+
     assert search_mode in [
         "optimal",
         "random",

pyomo/contrib/alternative_solutions/lp_enum_solnpool.py

@@ -104,7 +104,7 @@ def enumerate_linear_solutions_soln_pool(
     model : ConcreteModel
         A concrete Pyomo model
     num_solutions : int
-        The maximum number of solutions to generate.
+        The maximum number of solutions to generate. Must be positive.
     variables: None or a collection of Pyomo _GeneralVarData variables
         The variables for which bounds will be generated. None indicates
         that all variables will be included. Alternatively, a collection of
@@ -134,6 +134,10 @@ def enumerate_linear_solutions_soln_pool(
     """
     logger.info("STARTING LP ENUMERATION ANALYSIS USING GUROBI SOLUTION POOL")
 
+    assert num_solutions >= 1, "num_solutions must be positive integer"
+    if num_solutions == 1:
+        logger.warning("Running alternative_solutions method to find only 1 solution!")
+
     if poolmanager is None:
         poolmanager = PyomoPoolManager()
         poolmanager.add_pool("enumerate_binary_solutions", policy="keep_all")