Completed VRPPDTW and Improved Plotting

Author: danial-ch

.gitignore

@@ -162,5 +162,6 @@ cython_debug/
 **/Solution
 
 *.pdf
+*.docx
 
 *test*.py

Parsing.py

@@ -5,7 +5,8 @@ def get_full_graph(base_directory):
     nodes_file = base_directory + "Nodes.csv"
     edges_file = base_directory + "Edges.csv"
     requests = get_requests(base_directory + "Requests.csv")
-    graph = create_graph(nodes_file, edges_file, requests)
+    vehicles = get_vehicles(base_directory + "Vehicles.csv")
+    graph = create_graph(nodes_file, edges_file, requests, vehicles)
 
     return graph, requests
 
@@ -25,7 +26,7 @@ def convert_to_minutes(time_str):
     total_minutes = hours * 60 + minutes
     return total_minutes
 
-def read_nodes(nodes_file, requests):
+def read_nodes(nodes_file, requests, vehicles):
     nodes = {}
     with open(nodes_file, 'r') as file:
         reader = csv.reader(file)
@@ -42,7 +43,12 @@ def read_nodes(nodes_file, requests):
         origin, destination, count, _, _, _, _, _, _ = request
         nodes[origin]['node_type'] = 'Pickup Node'
         nodes[destination]['node_type'] = 'Delivery Node'
-        
+
+    for vehicle_id, vehicle in vehicles.items():
+        origin, destination, _ = vehicle
+        nodes[origin]['node_type'] = 'Depot Node'
+        nodes[destination]['node_type'] = 'Depot Node'
+
     return nodes
 
 def read_edges(filename):
@@ -56,10 +62,10 @@ def read_edges(filename):
                               'destination': int(target), 'travel_time': float(weight)}
     return edges
 
-def create_graph(nodes_file, edges_file, requests):
+def create_graph(nodes_file, edges_file, requests, vehicles):
     G = nx.DiGraph()
 
-    nodes = read_nodes(nodes_file, requests)
+    nodes = read_nodes(nodes_file, requests, vehicles)
     edges = read_edges(edges_file)
 
     for index, (key, value) in enumerate(nodes.items(), start=0):

Plot_Graph.py

@@ -17,13 +17,21 @@
 
 import os
 from pathlib import Path
+import sys
 from PIL import Image
+import keyboard
 from Parsing import get_full_graph
 import matplotlib.pyplot as plt
 import matplotlib.patches as mpatches
 import networkx as nx
 import json
 
+def get_node_label(node):
+    if node[1]['name'] != None:
+        return node[1]['name']
+    else:
+        return ""
+
 def base_graph(G, ax, pos, label_edges = True):
     # Draw nodes with different colors based on node types
     node_colors = []
@@ -33,15 +41,25 @@ def base_graph(G, ax, pos, label_edges = True):
             node_colors.append('green')
         elif 'node_type' in node_data[1] and node_data[1]['node_type'] == 'Delivery Node':
             node_colors.append('blue')
+        elif 'node_type' in node_data[1] and node_data[1]['node_type'] == 'Depot Node':
+            node_colors.append('red')
         else:
             node_colors.append('gray')  # Default color
         ax.text(pos[node][0], pos[node][1], str(node_data[1]['node_id']), fontsize=8, ha='center', va='center', color="white")
 
     nx.draw_networkx_nodes(G, pos, ax=ax, node_size=100, node_color=node_colors)
-    nx.draw_networkx_edges(G, pos, ax=ax, edge_color='black', width=1, arrows=False)
+    nx.draw_networkx_edges(G, pos, ax=ax, edge_color='black', width=0.5, arrows=False)
 
-    # Draw edge labels with weights
     if label_edges:
+        node_labels = {node[1]['node_id']: get_node_label(node) for node in G.nodes(data=True)}
+        for node, label in node_labels.items():
+            node_pos = pos[node]
+            x_offset = 0.5
+            y_offset = -0.8
+            label_pos = [node_pos[0] + x_offset, node_pos[1] + y_offset]
+            plt.text(*label_pos, label, ha='center', va='center', fontsize=6, 
+                    bbox=dict(boxstyle="round", facecolor='lightblue', alpha=0.3, edgecolor="none"))
+        
         edge_labels = nx.get_edge_attributes(G, 'weight')
         nx.draw_networkx_edge_labels(G, pos, ax=ax, edge_labels=edge_labels, font_size=7)
 
@@ -51,7 +69,7 @@ def base_graph(G, ax, pos, label_edges = True):
     center_x = (min(x_values) + max(x_values)) / 2
     center_y = (min(y_values) + max(y_values)) / 2
 
-    ax.grid(True, linestyle='-', linewidth=0.5, color='gray', zorder=0)
+    ax.grid(True, linestyle='-', linewidth=0.3, color='gray', zorder=0)
     # Set the x and y ticks with increments of 1
     x_ticks = range(int(min(x_values)), int(max(x_values)) + 1)
     y_ticks = range(int(min(y_values)), int(max(y_values)) + 1)
@@ -65,7 +83,8 @@ def base_graph(G, ax, pos, label_edges = True):
                       mpatches.Patch(color='blue', label='Delivery Node'),
                       mpatches.Patch(color='red', label='Depot Node'),
                       mpatches.Patch(color='gray', label='Junction Node')]
-    ax.legend(handles=legend_handles)
+    prop = {'size': 7}  # Adjust font size as needed
+    ax.legend(handles=legend_handles, prop=prop)
 
     return ax
 
@@ -80,18 +99,34 @@ def plot_overall_solution(graph, pos, solution_dir):
     with open(solution_dir + "chosen_x_ijk.json", "r") as json_file:
         chosen_x_ijk = json.load(json_file)
 
+    graph.remove_edges_from(list(graph.edges()))
+
+    bus_cnt = 0
     for bus, arc in chosen_x_ijk.items():
         fig, ax = plt.subplots(figsize=(8, 6))
-        ax = base_graph(graph, ax, pos, True)
-
-        graph.remove_edges_from(list(graph.edges()))
+        fig.suptitle('Bus ' + str(bus_cnt) , fontsize=20)
+        ax.clear()
         graph.add_edges_from(arc)
+        ax = base_graph(graph, ax, pos, False)
 
-        nx.draw_networkx_edges(graph, pos, ax=ax, edge_color='red', width=1, arrows=False)
+        nx.draw_networkx_edges(graph, pos, ax=ax,
+                               edge_color='red', width=1, arrows=True)
+        graph.remove_edges_from(arc)
+        bus_cnt += 1
 
     plt.show()
 
+space_pressed = False
+
+def on_key_press(event):
+    global space_pressed
+    if event.key == ' ':
+        space_pressed = True
+    elif event.key == 'q':
+        sys.exit()
+
 def plot_step_by_step(graph, pos, solution_dir, Gif=False):
+    global space_pressed
 
     # Read the JSON file
     with open(solution_dir + "buses_paths.json", "r") as json_file:
@@ -104,15 +139,49 @@ def plot_step_by_step(graph, pos, solution_dir, Gif=False):
 
     bus_cnt = 0
     for bus, movements in buses_paths.items():
+        total_cost = 0
         fig, ax = plt.subplots(figsize=(8, 6))
         fig.suptitle('Bus ' + str(bus_cnt) , fontsize=20)
+        fig.canvas.mpl_connect('key_press_event', on_key_press)
+        ax = base_graph(graph, ax, pos, False)
 
-        for idx, info in enumerate(movements):
+        valid_movements = []
+        for info in movements:
+            if len(info['path']) > 1:
+                valid_movements.append(info)
+
+        for idx, info in enumerate(valid_movements):
             paths = info['path']
             ax.clear()
-            ax = base_graph(graph, ax, pos, True)
+            ax = base_graph(graph, ax, pos, False)
+            y_lim = plt.ylim()
+            x_lim = plt.xlim()
+            plt.ylim(y_lim[0], y_lim[1] * 1.2)
+
+            x_center = (x_lim[0] + x_lim[1]) / 2
 
             if Gif:
+                text = info['status']
+                plt.text(x_center, y_lim[1] * 1.1, text, ha='center', va='center', 
+                         fontsize=10, color='white',
+                    bbox=dict(boxstyle="round", facecolor='black', edgecolor="none"))
+
+                load_text = f"Load : {info['start_load']} -> {info['finish_load']}"
+                plt.text(x_lim[0], y_lim[1] * 1.15, load_text, ha='left', 
+                         va='center', fontsize=8, color='white',
+                    bbox=dict(boxstyle="round", facecolor='purple', edgecolor="none"))
+                
+                time_text = f"Time : {info['start_time']} -> {info['finish_time']}"
+                plt.text(x_lim[0], y_lim[1] * 1.05, time_text, ha='left', 
+                         va='center', fontsize=8, color='white',
+                         bbox=dict(boxstyle="round", facecolor='blue', edgecolor="none"))
+                
+                total_cost += int(info['path_cost'])
+                cost_text = f"Cost : {info['path_cost']} - total Cost : {total_cost}"
+                plt.text(x_lim[0], y_lim[1] * 0.95, cost_text, ha='left', 
+                         va='center', fontsize=8, color='white',
+                         bbox=dict(boxstyle="round", facecolor='brown', edgecolor="none"))
+                    
                 edges = list(zip(paths, paths[1:]))
                 nx.draw_networkx_edges(graph, pos, edgelist=edges, ax=ax, edge_color='r', 
                                        width=2, arrows=True)
@@ -121,38 +190,53 @@ def plot_step_by_step(graph, pos, solution_dir, Gif=False):
                 fig.savefig(frame_filename)
 
             else:
-                if idx == 0:
-                    plt.pause(2)
-                elif idx == len(movements) - 1:
-                    edges = []
-                    for segment in movements:
-                        path = segment['path']
-                        if len(path) > 2:
-                            for i in range(len(path) - 1):
-                                edges.append((path[i],path[i+1]))
-                        elif len(path) == 2:
-                            edges.append(tuple(path))
-                    nx.draw_networkx_edges(graph, pos, edgelist=edges, ax=ax, edge_color='r', width=2, arrows=False)
-                else:
-                    edges = list(zip(paths, paths[1:]))
-                    nx.draw_networkx_edges(graph, pos, edgelist=edges, ax=ax, edge_color='r', width=2, arrows=True)
-                plt.pause(1)
+                text = info['status']
+                plt.text(x_center, y_lim[1] * 1.1, text, ha='center', va='center', 
+                            fontsize=10, color='white',
+                    bbox=dict(boxstyle="round", facecolor='black', edgecolor="none"))
+
+                load_text = f"Load : {info['start_load']} -> {info['finish_load']}"
+                plt.text(x_lim[0], y_lim[1] * 1.15, load_text, ha='left', 
+                            va='center', fontsize=8, color='white',
+                    bbox=dict(boxstyle="round", facecolor='purple', edgecolor="none"))
+                
+                time_text = f"Time : {info['start_time']} -> {info['finish_time']}"
+                plt.text(x_lim[0], y_lim[1] * 1.05, time_text, ha='left', 
+                            va='center', fontsize=8, color='white',
+                    bbox=dict(boxstyle="round", facecolor='blue', edgecolor="none"))
+                
+                total_cost += int(info['path_cost'])
+                cost_text = f"Cost : {info['path_cost']} - total Cost : {total_cost}"
+                plt.text(x_lim[0], y_lim[1] * 0.95, cost_text, ha='left', 
+                         va='center', fontsize=8, color='white',
+                         bbox=dict(boxstyle="round", facecolor='brown', edgecolor="none"))
+                
+                edges = list(zip(paths, paths[1:]))
+                nx.draw_networkx_edges(graph, pos, edgelist=edges, ax=ax, edge_color='r', 
+                                        width=2, arrows=True)
+
+                while not space_pressed:
+                    plt.pause(0.1)
+                space_pressed = False
 
         if Gif:
-            frames = [Image.open(f'{gif_dir}/{frame}') for frame in sorted(os.listdir(gif_dir)) if frame.endswith(".png")]
+            frames = [Image.open(f'{gif_dir}/{frame}') for frame in sorted(os.listdir(gif_dir)) 
+                      if frame.endswith(".png")]
             gif_filename = f'{gif_dir}/bus_{bus}.gif'
             frames[0].save(gif_filename, format='GIF', append_images=frames[1:], 
                         save_all=True, duration=1000, loop=0)
             [f.unlink() for f in Path(gif_dir).glob("*") if f.name.endswith(".png")] 
 
         bus_cnt += 1
+        plt.close(fig)
 
     if not Gif:
         plt.show()
 
 def main():
     # Specify the folder name under the Inputs folder
-    problem_dir = input("\nEnter folder name of the problem\n")
+    print("-------------")
+    problem_dir = input("Enter folder name of the problem\n")
 
     base_directory = "Samples/" + problem_dir + "/"
     solution_dir = base_directory + "Solution/"

VRPPDTW.py

@@ -346,6 +346,7 @@ def optimize_model(vehicles : dict, requests : dict, graph : DiGraph) -> dict:
                                          "start_load" : round(solution.get_value(L[i, k])),
                                          "finish_load" : round(solution.get_value(L[j, k])),
                                          "path" : shortest_paths_dict[V_val[k][i]][V_val[k][j]],
+                                         "path_cost" : t[V_val[k][i]][V_val[k][j]],
                                          "status" : status}
 
                     # Storing chosen arcs from X
@@ -377,13 +378,14 @@ def optimize_model(vehicles : dict, requests : dict, graph : DiGraph) -> dict:
 def main():
 
     # Specify the folder name under the Inputs folder
-    problem_dir = input("\nEnter folder name of the problem\n")
+    print("-------------")
+    problem_dir = input("Enter folder name of the problem\n")
 
     # Read input data including vehicles, request, nodes and edges
     base_directory = "Samples/" + problem_dir + "/"
     vehicles = get_vehicles(base_directory + "Vehicles.csv")
     requests = get_requests(base_directory + "Requests.csv")
-    graph = create_graph(base_directory + "Nodes.csv",base_directory + "Edges.csv", requests)
+    graph = create_graph(base_directory + "Nodes.csv",base_directory + "Edges.csv", requests, vehicles)
 
     buses_paths, chosen_X, chosen_T, chosen_L = optimize_model(vehicles, requests, graph)