notebooks: sync

examples/notebook/constraint_solver/vrp_initial_routes.ipynb

@@ -83,6 +83,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "from ortools.constraint_solver import routing_enums_pb2\n",
     "from ortools.constraint_solver import pywrapcp\n",
     "\n",
     "\n",
@@ -229,14 +230,23 @@
     "    distance_dimension = routing.GetDimensionOrDie(dimension_name)\n",
     "    distance_dimension.SetGlobalSpanCostCoefficient(100)\n",
     "\n",
+    "    # Close model with the custom search parameters.\n",
+    "    search_parameters = pywrapcp.DefaultRoutingSearchParameters()\n",
+    "    search_parameters.first_solution_strategy = (\n",
+    "        routing_enums_pb2.FirstSolutionStrategy.PATH_CHEAPEST_ARC)\n",
+    "    search_parameters.local_search_metaheuristic = (\n",
+    "        routing_enums_pb2.LocalSearchMetaheuristic.GUIDED_LOCAL_SEARCH)\n",
+    "    search_parameters.time_limit.FromSeconds(5)\n",
+    "    # When an initial solution is given for search, the model will be closed with the default\n",
+    "    # search parameters unless it is explicitly closed with the custom search parameters.\n",
+    "    routing.CloseModelWithParameters(search_parameters)\n",
+    "\n",
+    "    # Get initial solution from routes after closing the model.\n",
     "    initial_solution = routing.ReadAssignmentFromRoutes(data['initial_routes'],\n",
     "                                                        True)\n",
     "    print('Initial solution:')\n",
     "    print_solution(data, manager, routing, initial_solution)\n",
     "\n",
-    "    # Set default search parameters.\n",
-    "    search_parameters = pywrapcp.DefaultRoutingSearchParameters()\n",
-    "\n",
     "    # Solve the problem.\n",
     "    solution = routing.SolveFromAssignmentWithParameters(\n",
     "        initial_solution, search_parameters)\n",

examples/notebook/contrib/production.ipynb

@@ -94,10 +94,10 @@
     "from ortools.linear_solver import pywraplp\n",
     "\n",
     "\n",
-    "def main(sol='CBC'):\n",
+    "def main():\n",
     "\n",
     "  # Create the solver.\n",
-    "  solver = pywraplp.Solver.CreateSolver(sol)\n",
+    "  solver = pywraplp.Solver.CreateSolver('glop')\n",
     "  if not solver:\n",
     "    return\n",
     "\n",
@@ -169,15 +169,7 @@
     "  print()\n",
     "\n",
     "\n",
-    "\n",
-    "sol = 'CBC'\n",
-    "if len(sys.argv) > 1:\n",
-    "  sol = sys.argv[1]\n",
-    "  if sol != 'GLPK' and sol != 'CBC':\n",
-    "    print('Solver must be either GLPK or CBC')\n",
-    "    sys.exit(1)\n",
-    "\n",
-    "main(sol)\n",
+    "main()\n",
     "\n"
    ]
   }

examples/notebook/examples/arc_flow_cutting_stock_sat.ipynb

@@ -273,8 +273,9 @@
     "    item_coeffs = collections.defaultdict(list)\n",
     "\n",
     "    start_time = time.time()\n",
-    "    solver = pywraplp.Solver('Steel',\n",
-    "                             pywraplp.Solver.CBC_MIXED_INTEGER_PROGRAMMING)\n",
+    "    solver = pywraplp.Solver.CreateSolver('cbc')\n",
+    "    if not solver:\n",
+    "        return\n",
     "\n",
     "    objective_vars = []\n",
     "    objective_coeffs = []\n",

examples/notebook/examples/knapsack_2d_sat.ipynb

@@ -97,9 +97,10 @@
     "\n",
     "_OUTPUT_PROTO = flags.DEFINE_string(\n",
     "    'output_proto', '', 'Output file to write the cp_model proto to.')\n",
-    "_PARAMS = flags.DEFINE_string('params',\n",
-    "                              'num_search_workers:16,log_search_progress:true',\n",
-    "                              'Sat solver parameters.')\n",
+    "_PARAMS = flags.DEFINE_string(\n",
+    "    'params',\n",
+    "    'num_search_workers:16,log_search_progress:true,max_time_in_seconds:10.0',\n",
+    "    'Sat solver parameters.')\n",
     "_MODEL = flags.DEFINE_string('model', 'rotation',\n",
     "                             '\\'duplicate\\' or \\'rotation\\' or \\'optional\\'')\n",
     "\n",

examples/notebook/examples/prize_collecting_tsp_sat.ipynb

@@ -220,9 +220,9 @@
     "    # Solve and print out the solution.\n",
     "    solver = cp_model.CpSolver()\n",
     "    # To benefit from the linearization of the circuit constraint.\n",
-    "    solver.parameters.linearization_level = 2\n",
     "    solver.parameters.max_time_in_seconds = 15.0\n",
-    "    #solver.parameters.log_search_progress = True\n",
+    "    solver.parameters.num_search_workers = 8\n",
+    "    # solver.parameters.log_search_progress = True\n",
     "\n",
     "    solver.Solve(model)\n",
     "    #print(solver.ResponseStats())\n",

examples/notebook/examples/prize_collecting_vrp_sat.ipynb

@@ -236,7 +236,7 @@
     "    solver = cp_model.CpSolver()\n",
     "    solver.parameters.num_search_workers = 8\n",
     "    solver.parameters.max_time_in_seconds = 15.0\n",
-    "    #solver.parameters.log_search_progress = True\n",
+    "    # solver.parameters.log_search_progress = True\n",
     "\n",
     "    status = solver.Solve(model)\n",
     "    if status == cp_model.FEASIBLE or status == cp_model.OPTIMAL:\n",