Merge pull request #459 from AI4Finance-Foundation/r12d

vrptw
AI4Finance-Foundation · Nov 12, 2024 · 3697adc · 3697adc
2 parents 90bec47 + fbf8f54
commit 3697adc
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Showing 11 changed files with 34 additions and 34 deletions.
diff --git a/rlsolver/beta1.py b/rlsolver/beta1.py
diff --git a/rlsolver/methods/VRPTW_algs/ESPPRC2.py b/rlsolver/methods/VRPTW_algs/ESPPRC2.py
@@ -27,7 +27,7 @@
                                               calc_dist_of_path,
                                               obtain_paths_based_on_vehicles,
                                               calc_demands_of_paths,
-                                              obtai_var_vals,
+                                              obtain_var_vals,
                                               calc_durations_of_paths, )
 from Label import Label
 from util import (read_data_as_nxdigraph,
@@ -198,7 +198,7 @@ def opt_arc_bounding_model(duration_lowerbound_dict: dict, duration_to_depot: fl
     obj = model.ObjVal if feasible else None
 
     var_name: str = "y"
-    y_vals = obtai_var_vals(model, var_name) if feasible else None
+    y_vals = obtain_var_vals(model, var_name) if feasible else None
     return y_vals, obj, feasible
 
 

diff --git a/rlsolver/methods/VRPTW_algs/ESPPRC_demo.py b/rlsolver/methods/VRPTW_algs/ESPPRC_demo.py
@@ -4,11 +4,13 @@
 import copy
 from typing import List, Tuple, Set, Dict
 
+
 class Label:
     path = []
     travel_time = 0
     dist = 0
 
+
 # dominance rule
 def dominate(labels: List[Label], path_dict: Dict[int, Label]):
     labels_copy = copy.deepcopy(labels)
@@ -35,8 +37,6 @@ def dominate(labels: List[Label], path_dict: Dict[int, Label]):
     return labels, path_dict
 
 
-
-
 # labeling algorithm
 def labeling_SPPRC(graph, orig, dest):
     # initial Q
@@ -135,6 +135,6 @@ def main():
     print('optimal path : ', opt_path[1].path)
     print('optimal path (dist): ', opt_path[1].dist)
 
+
 if __name__ == '__main__':
     main()
-
diff --git a/rlsolver/methods/VRPTW_algs/ESPPRC_demo2.py b/rlsolver/methods/VRPTW_algs/ESPPRC_demo2.py
@@ -4,6 +4,7 @@
 import copy
 from typing import List, Tuple, Set, Dict
 
+
 class Label:
     path = []
     duration = 0
@@ -42,6 +43,7 @@ def make_unique(labels) -> List:
                 res.append(labels[i])
         return res
 
+
 # dominance rule
 def EFF(labels2: List[Label]):
     labels = Label.make_unique(labels2)
@@ -75,8 +77,6 @@ def EFF(labels2: List[Label]):
     return filtered_labels
 
 
-
-
 # labeling algorithm
 def labeling_SPPRC(graph, orig, dest):
     # initial Q
@@ -175,6 +175,6 @@ def main():
         print(f'The {i + 1}-th optimal path (time): {opt_label.duration}')
     print()
 
+
 if __name__ == '__main__':
     main()
-
diff --git a/rlsolver/methods/VRPTW_algs/ESPPRC_demo3.py b/rlsolver/methods/VRPTW_algs/ESPPRC_demo3.py
@@ -4,7 +4,6 @@
 rlsolver_path = os.path.join(cur_path, '../../../rlsolver')
 sys.path.append(os.path.dirname(rlsolver_path))
 
-import numpy as np
 import networkx as nx
 import copy
 from typing import List, Tuple, Union, Dict

diff --git a/rlsolver/methods/VRPTW_algs/Label.py b/rlsolver/methods/VRPTW_algs/Label.py
@@ -126,6 +126,7 @@ def dominate(self, another, forward: bool):
                 return False
 
     @staticmethod
+    # keep non-dominated labels
     def EFF(labels2: List, forward: bool) -> List:
         labels = Label.make_unique(labels2)
         if len(labels) <= 1:

diff --git a/rlsolver/methods/VRPTW_algs/Vehicle.py b/rlsolver/methods/VRPTW_algs/Vehicle.py
@@ -1,5 +1,6 @@
 import sys
 import os
+
 cur_path = os.path.dirname(os.path.abspath(__file__))
 rlsolver_path = os.path.join(cur_path, '../../../rlsolver')
 sys.path.append(os.path.dirname(rlsolver_path))

diff --git a/rlsolver/methods/VRPTW_algs/column_generation.py b/rlsolver/methods/VRPTW_algs/column_generation.py
@@ -28,7 +28,7 @@
                                               calc_demands_of_paths,
                                               calc_durations_of_paths,
                                               obtain_paths_based_on_vehicles,
-                                              obtai_var_vals,
+                                              obtain_var_vals,
                                               )
 from rlsolver.methods.VRPTW_algs.ESPPRC1 import ESPPRC1_unidirectional
 from rlsolver.methods.VRPTW_algs.config import Config
@@ -269,7 +269,7 @@ def run_column_generation():
             if max_dist - min_dist <= Config.CHECK_DIFF_THRESHOLD_IN_CG:
                 break
 
-        theta_vals_this_iteration = obtai_var_vals(model, "theta")
+        theta_vals_this_iteration = obtain_var_vals(model, "theta")
         theta_valss.append(theta_vals_this_iteration)
         print(f"theta_vals_this_iteration: {theta_vals_this_iteration}")
 
@@ -330,7 +330,7 @@ def run_column_generation():
     else:
         raise ValueError
 
-    theta_vals = obtai_var_vals(model, "theta")
+    theta_vals = obtain_var_vals(model, "theta")
     theta_vals_in_set = set(theta_vals)
     print(f"theta_vals: {theta_vals}")
     print(f"theta_vals_in_set: {theta_vals_in_set}")

diff --git a/rlsolver/methods/VRPTW_algs/impact_heuristic.py b/rlsolver/methods/VRPTW_algs/impact_heuristic.py
@@ -1,6 +1,7 @@
 # The impact heuristic is implemented based on the paper "A greedy look-ahead heuristic for the vehicle routing problem with time windows"
 import sys
 import os
+
 cur_path = os.path.dirname(os.path.abspath(__file__))
 rlsolver_path = os.path.join(cur_path, '../../../rlsolver')
 sys.path.append(os.path.dirname(rlsolver_path))
@@ -12,19 +13,19 @@
 import networkx as nx
 
 from rlsolver.methods.VRPTW_algs.Customer import (Customer,
-                      )
+                                                  )
 from rlsolver.methods.VRPTW_algs.Vehicle import Vehicle
 from rlsolver.methods.VRPTW_algs.util import (read_data,
-                  read_data_as_nxdigraph,
-                  generate_vehicles,
-                  generate_vehicles_and_assign_paths,
-                  obtain_paths_based_on_vehicles,
-                  calc_demands_of_paths,
-                  calc_durations_of_paths,
-                  calc_dists_of_paths,
-                  write_result,
-                  write_result_based_on_vehicles,
-                  )
+                                              read_data_as_nxdigraph,
+                                              generate_vehicles,
+                                              generate_vehicles_and_assign_paths,
+                                              obtain_paths_based_on_vehicles,
+                                              calc_demands_of_paths,
+                                              calc_durations_of_paths,
+                                              calc_dists_of_paths,
+                                              write_result,
+                                              write_result_based_on_vehicles,
+                                              )
 
 from rlsolver.methods.VRPTW_algs.config import Config
 

diff --git a/rlsolver/methods/VRPTW_algs/util.py b/rlsolver/methods/VRPTW_algs/util.py
@@ -423,7 +423,7 @@ def filter_vehicles_based_on_paths(vehicles2: List[Vehicle], paths: List[str], c
     #     res.append(vehicle)
     # return res
 
-def obtai_var_vals(model, var_name: str):
+def obtain_var_vals(model, var_name: str):
     theta_vals = []
     num_vars = model.NumVars
     for i in range(num_vars):

diff --git a/rlsolver/methods/genetic_algorithm.py b/rlsolver/methods/genetic_algorithm.py
@@ -1,12 +1,14 @@
 import sys
 import os
+
 cur_path = os.path.dirname(os.path.abspath(__file__))
 rlsolver_path = os.path.join(cur_path, '../../rlsolver')
 sys.path.append(os.path.dirname(rlsolver_path))
 
 import random
 import os
-os.environ['KMP_DUPLICATE_LIB_OK']='True'
+
+os.environ['KMP_DUPLICATE_LIB_OK'] = 'True'
 import copy
 import time
 import numpy as np
@@ -20,13 +22,13 @@
     plt = None
 
 from rlsolver.methods.util import (calc_txt_files_with_prefixes,
-                                    )
+                                   )
 from rlsolver.methods.util_read_data import (read_nxgraph,
-                                            )
+                                             )
 from rlsolver.methods.util_obj import (obj_maxcut,
-                                        )
+                                       )
 from rlsolver.methods.util_result import (write_graph_result,
-                                         )
+                                          )
 
 # constants for tabuSearch
 P_iter = 100
@@ -161,7 +163,6 @@ def tabu_search(initial_solution, graph):
     return best_solution, best_score
 
 
-
 def cross_over(population, graph):
     selected_parents = random.sample(population, num_parents)
 
@@ -210,8 +211,7 @@ def genetic_maxcut(graph: nx.Graph(), filename):
     print("Genetic Search Complete")
 
 
-
-def run_genetic_over_multiple_files(directory_data: str, prefixes: List[str])-> List[List[float]]:
+def run_genetic_over_multiple_files(directory_data: str, prefixes: List[str]) -> List[List[float]]:
     assert PROBLEM == Problem.maxcut
     scoress = []
     files = calc_txt_files_with_prefixes(directory_data, prefixes)