New Inventory type for TD

[optf/has.git] / conductor / conductor / solver / optimizer / optimizer.py

diff --git a/conductor/conductor/solver/optimizer/optimizer.py b/conductor/conductor/solver/optimizer/optimizer.py
index a36124c..7909c15 100755 (executable)
--- a/conductor/conductor/solver/optimizer/optimizer.py
+++ b/conductor/conductor/solver/optimizer/optimizer.py
@@ -22,7 +22,6 @@ from oslo_log import log
 import copy
 import time
 
-
 from conductor import service
 # from conductor.solver.optimizer import decision_path as dpath
 # from conductor.solver.optimizer import best_first
@@ -74,7 +73,7 @@ class Optimizer(object):
 
     def get_solution(self, num_solutions):
 
-        LOG.debug("search start")
+        LOG.debug("search start for max {} solutions".format(num_solutions))
         for rk in self.requests:
             request = self.requests[rk]
             LOG.debug("--- request = {}".format(rk))
@@ -88,7 +87,8 @@ class Optimizer(object):
 
             LOG.debug("2. search")
 
-            while (num_solutions == 'all' or num_solutions > 0):
+            rand_counter = 10
+            while num_solutions == 'all' or num_solutions > 0:
 
                 LOG.debug("searching for the solution {}".format(len(decision_list) + 1))
 
@@ -106,19 +106,28 @@ class Optimizer(object):
                     best_path = self.search.search(demand_list,
                                                    request.objective, request)
 
+                LOG.debug("search delay = {} sec".format(time.time() - st))
+
+                demand_list = copy.deepcopy(_copy_demand_list)
+
                 if best_path is not None:
                     self.search.print_decisions(best_path)
+                    rand_counter = 10
+                elif not request.objective.goal and rand_counter > 0 and self._has_candidates(request):
+                    # RandomPick gave no candidates after applying constraints. If there are any candidates left
+                    # lets' try again several times until some solution is found. When one of the demands is not unique
+                    # it persists in the list all the time. In order to prevent infinite loop we need to have counter
+                    rand_counter -= 1
+                    LOG.debug("Incomplete random solution - repeat {}".format(rand_counter))
+                    continue
                 else:
                     LOG.debug("no solution found")
                     break
 
-                LOG.debug("search delay = {} sec".format(time.time() - st))
-
                 # add the current solution to decision_list
                 decision_list.append(best_path.decisions)
 
                 #remove the candidate with "uniqueness = true"
-                demand_list = copy.deepcopy(_copy_demand_list)
                 self._remove_unique_candidate(request, best_path, demand_list)
 
                 if num_solutions != 'all':
@@ -126,6 +135,15 @@ class Optimizer(object):
             self.search.triageSolver.getSolution(decision_list)
             return decision_list
 
+    def _has_candidates(self, request):
+        for demand_name, demand in request.demands.items():
+            LOG.debug("Req Available resources: {} {}".format(demand_name, len(request.demands[demand_name].resources)))
+            if len(demand.resources) == 0:
+                LOG.debug("No more candidates for demand {}".format(demand_name))
+                return False
+
+        return True
+
     def _remove_unique_candidate(self, _request, current_decision, demand_list):
 
         # This method is to remove previous solved/used candidate from consideration