{ "cells": [ { "attachments": {}, "cell_type": "markdown", "id": "83c2b1e7-b401-4a15-adf0-d43cebf9ad81", "metadata": {}, "source": [ "# Projet algorithme # \n" ] }, { "attachments": {}, "cell_type": "markdown", "id": "0b4f92e5-ac40-4491-983d-890c4f0f6694", "metadata": {}, "source": [ "## Contexte du projet: \n" ] }, { "attachments": {}, "cell_type": "markdown", "id": "5f483b31-1246-4f00-ae39-718ef92ce9eb", "metadata": {}, "source": [ "L'ADEME a lancé un appel à manifestation d'intérêt pour développer des solutions de mobilité adaptées à différents territoires. CesiCDP, en collaboration avec des partenaires, s'est spécialisé dans la Mobilité Multimodale Intelligente. Dans le cadre de cet appel, l'équipe de CesiCDP travaille sur la gestion de tournées de livraison pour minimiser les trajets et optimiser l'efficacité. L'objectif est d'obtenir de nouveaux marchés et des financements pour poursuivre le développement de l'entreprise. Des contraintes supplémentaires seront ajoutées pour rendre le problème plus réaliste et intéressant pour l'ADEME." ] }, { "attachments": {}, "cell_type": "markdown", "id": "fc23daaf-9f25-4c5a-bf6c-300a7ed8d623", "metadata": {}, "source": [ "Notre but est de réaliser un algorithme permettant de passer par tous les points de livraisons avec un temps optimisé." ] }, { "attachments": {}, "cell_type": "markdown", "id": "d633beb7-8f26-46d4-9cd9-1d0093e5b5c3", "metadata": {}, "source": [ "## Contrainte choisie :\n" ] }, { "attachments": {}, "cell_type": "markdown", "id": "35fc1c3c-d7a9-4423-a948-aa00ab51dbf4", "metadata": {}, "source": [ "La contrainte que nous avons choisi est la suivante:\n", "- Avoir plusieurs camions disponibles simultanément pour effectuer les livraisons.\n" ] }, { "attachments": {}, "cell_type": "markdown", "id": "ba356166-604a-4627-ac0f-93b76eb7a22d", "metadata": {}, "source": [ "## Formulation du problème" ] }, { "attachments": {}, "cell_type": "markdown", "id": "c4d6888b-14e6-4745-880f-0a063ebf7476", "metadata": {}, "source": [ "Soit un graphe $G=(V,E)$, où $V$ est l'ensemble des villes (ou points de livraison) et $E$ est l'ensemble des routes entre les villes. Il y a $k$ camions disponibles pour effectuer les livraisons.\n", "\n", "Le problème consiste à trouver une tournée pour chaque camion, de manière à ce que toutes les livraisons soient effectuées en un temps minimum tout en partant et en revenant au dépôt.\n", "\n", "Le problème que nous avons avec les contraintes ci-dessus est le problème du VRP (Vehicule Routing Problem)." ] }, { "attachments": {}, "cell_type": "markdown", "id": "6d392f68", "metadata": {}, "source": [ "## Contraintes du problème" ] }, { "attachments": {}, "cell_type": "markdown", "id": "f95dba22", "metadata": {}, "source": [ "Liste des contraintes du problème:\n", "\n", "- Tous les clients doivent être déservis\n", "- Un client ne peut être servi que par un et un seul véhicule.\n", "- En quittant un client, un véhicule peut aller que vers un seul autre client.\n", "\n", "On va donc affecter chaque client à une tournée effectué par un seul véhicule." ] }, { "attachments": {}, "cell_type": "markdown", "id": "16b3b8a7-4658-4509-a511-7a395654e6f1", "metadata": {}, "source": [ "## Modélisation mathématique" ] }, { "attachments": {}, "cell_type": "markdown", "id": "b54bfa8c", "metadata": {}, "source": [ "### Ensemble et paramètres:" ] }, { "attachments": {}, "cell_type": "markdown", "id": "637eb295", "metadata": {}, "source": [ "$V=\\{0,1,2,...,n\\}$ : l'ensemble des villes, où 0 est la base (le dépôt) et $1,2,...,n$ sont les villes de livraison.
\n", "$K=\\{1,2,...,k\\}$ : l'ensemble des camions.
\n", "$d_{ij}$​ : la distance (ou le temps de trajet) de la ville $i$ à la ville $j$.
\n", "$M$ : une grande constante." ] }, { "attachments": {}, "cell_type": "markdown", "id": "1219e4f2", "metadata": {}, "source": [ "### Variables de décision:" ] }, { "attachments": {}, "cell_type": "markdown", "id": "a6d398fa", "metadata": {}, "source": [ "$x_{ijk}$​ : variable binaire qui vaut 1 si le camion $k$ se déplace de la ville $i$ à la ville $j$, et 0 sinon.
\n", "$t_{ik}$​ : le moment où le camion $k$ arrive à la ville $i$." ] }, { "attachments": {}, "cell_type": "markdown", "id": "e635cf14", "metadata": {}, "source": [ "### Fonction objective:" ] }, { "attachments": {}, "cell_type": "markdown", "id": "56652859", "metadata": {}, "source": [ "Minimiser $Z=max_{⁡k∈K}t_{0k}​$" ] }, { "attachments": {}, "cell_type": "markdown", "id": "a1465000", "metadata": {}, "source": [ "### Contraintes:\n", "Chaque ville est visitée une fois et une seule fois : $$\\sum_{⁡k∈K} \\sum_{⁡j∈V} x_{ijk} = 1, ∀i \\in V∖ \\{0\\}$$\n", "\n", "Si un camion se déplace de la ville ii à la ville $j$, alors le moment d'arrivée à la ville $j$ doit être plus grand que le moment d'arrivée à la ville $i$ plus le temps de trajet : $$t_{ik}​+d_{ij}​ \\leq t_{jk}​+M(1−x_{ijk}​),∀i,j \\in V,i \\ne j,∀k \\in K$$\n", "\n", "Les fenêtres de temps de livraison doivent être respectées : $$a_i​ \\leq t_{ik}​ \\leq b_i​, ∀i \\in V∖ \\{0 \\},∀k \\in K$$\n", "\n", "Les contraintes de flux pour garantir que si un camion entre dans une ville, il doit également en sortir :\n", "$$i \\in V,i \\ne j∑​xijk​=i∈V,i \\ne j∑​xjik​=yjk​,∀j∈V,∀k∈K$$" ] }, { "attachments": {}, "cell_type": "markdown", "id": "286caeb7-26cb-486a-b5f0-94a3f24811fd", "metadata": {}, "source": [ "Nous allons représenter notre problème par un graphe
\n", "$G=(V,E)$\n", "\n", "$V$ représente les sommets du graphe qui correspondent aux clients\n", "\n", "$E$ représente les arcs entre deux clients $i,j \\in V$\n", "\n", "\n", "\n", "On a un ensemble $C=\\{1,2,...,n_c\\}$ de clients qui doivent obtenir leur livraison qui provient du dépot.\n", "\n", "\n", "L'ensemble des emplacements des clients est défini comme :\n", "$V = C \\cup \\{0, n_c+1\\} $\n", "\n", "$0$ et $n_c+1$ représente le dépot, puisqu'on doit revenir au point de départ le dépots est le dernier client plus un. \n", "\n", "\n", "On a un ensemble $V=\\{1,2,...,n_v\\}$ de véhicule disponible et chaque véhicule possède une capacité $Q$.\n", "\n", "\n", "\n", "# Variables de décisions: \n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n" ] }, { "attachments": {}, "cell_type": "markdown", "id": "5a3512bc-02da-4e2d-b8f6-65e70c3fe686", "metadata": {}, "source": [ "Variables de décision:\n", "- Un ensemble de k véhicule\n" ] }, { "attachments": {}, "cell_type": "markdown", "id": "7670fdf4-884c-4352-83fa-eed0c8b50074", "metadata": {}, "source": [ "# Initialisation de la matrice" ] }, { "cell_type": "code", "execution_count": 1, "id": "c177ac22", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[[0. 1. 1. 2. 2. 2. 2. 2. 1. 2. 2. 3. 2. 2. 2. 1. 1. 2. 1. 3. 2.]\n", " [1. 0. 2. 1. 2. 2. 1. 2. 1. 2. 2. 3. 3. 2. 3. 2. 2. 1. 2. 2. 2.]\n", " [1. 2. 0. 2. 1. 2. 2. 3. 2. 1. 3. 2. 3. 1. 2. 2. 2. 3. 2. 2. 2.]\n", " [2. 1. 2. 0. 2. 3. 2. 2. 1. 2. 2. 2. 2. 1. 2. 3. 3. 1. 1. 1. 2.]\n", " [2. 2. 1. 2. 0. 3. 3. 3. 1. 2. 2. 3. 4. 2. 1. 3. 3. 3. 2. 3. 2.]\n", " [2. 2. 2. 3. 3. 0. 1. 2. 3. 1. 2. 1. 2. 2. 4. 1. 1. 3. 3. 2. 3.]\n", " [2. 1. 2. 2. 3. 1. 0. 3. 2. 1. 3. 2. 3. 3. 4. 2. 2. 2. 3. 2. 3.]\n", " [2. 2. 3. 2. 3. 2. 3. 0. 2. 3. 1. 2. 3. 3. 4. 1. 2. 1. 3. 3. 3.]\n", " [1. 1. 2. 1. 1. 3. 2. 2. 0. 3. 1. 2. 3. 2. 2. 2. 2. 2. 2. 2. 1.]\n", " [2. 2. 1. 2. 2. 1. 1. 3. 3. 0. 3. 2. 2. 2. 3. 2. 2. 3. 3. 1. 2.]\n", " [2. 2. 3. 2. 2. 2. 3. 1. 1. 3. 0. 1. 4. 2. 3. 2. 3. 2. 3. 3. 2.]\n", " [3. 3. 2. 2. 3. 1. 2. 2. 2. 2. 1. 0. 3. 1. 3. 2. 2. 3. 2. 3. 2.]\n", " [2. 3. 3. 2. 4. 2. 3. 3. 3. 2. 4. 3. 0. 3. 4. 2. 1. 3. 3. 1. 2.]\n", " [2. 2. 1. 1. 2. 2. 3. 3. 2. 2. 2. 1. 3. 0. 2. 3. 3. 2. 1. 2. 1.]\n", " [2. 3. 2. 2. 1. 4. 4. 4. 2. 3. 3. 3. 4. 2. 0. 3. 3. 3. 1. 3. 3.]\n", " [1. 2. 2. 3. 3. 1. 2. 1. 2. 2. 2. 2. 2. 3. 3. 0. 1. 2. 2. 3. 3.]\n", " [1. 2. 2. 3. 3. 1. 2. 2. 2. 2. 3. 2. 1. 3. 3. 1. 0. 3. 2. 2. 3.]\n", " [2. 1. 3. 1. 3. 3. 2. 1. 2. 3. 2. 3. 3. 2. 3. 2. 3. 0. 2. 2. 3.]\n", " [1. 2. 2. 1. 2. 3. 3. 3. 2. 3. 3. 2. 3. 1. 1. 2. 2. 2. 0. 2. 2.]\n", " [3. 2. 2. 1. 3. 2. 2. 3. 2. 1. 3. 3. 1. 2. 3. 3. 2. 2. 2. 0. 1.]\n", " [2. 2. 2. 2. 2. 3. 3. 3. 1. 2. 2. 2. 2. 1. 3. 3. 3. 3. 2. 1. 0.]]\n", "[[0 1 1 0 0 0 0 0 1 0 0 0 0 0 0 1 1 0 1 0 0]\n", " [1 0 0 1 0 0 1 0 1 0 0 0 0 0 0 0 0 1 0 0 0]\n", " [1 0 0 0 1 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0]\n", " [0 1 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 1 1 1 0]\n", " [0 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "\n", "import random\n", "import numpy as np\n", "import networkx as nx\n", "import matplotlib.pyplot as plt\n", "\n", "def generate_graph(num_nodes):\n", " G = nx.Graph()\n", " G.add_nodes_from(range(num_nodes + 1))\n", " \n", " for node in G.nodes():\n", " connected_nodes = sorted(set(G.nodes()) - {node})\n", " if len(connected_nodes) < 2:\n", " continue\n", " distance1 = random.randint(1, 10)\n", " distance2 = random.randint(1, 10)\n", " random_nodes = random.sample(connected_nodes, 2)\n", " G.add_edges_from([(node, random_nodes[0], {'distance': distance1}),\n", " (node, random_nodes[1], {'distance': distance2})])\n", "\n", " while not nx.is_connected(G):\n", " node1, node2 = random.sample(G.nodes(), 2)\n", " if not G.has_edge(node1, node2):\n", " distance = random.randint(1, 10)\n", " G.add_edge(node1, node2, distance=distance)\n", "\n", " # Assigner des positions aléatoires aux nœuds\n", " pos = {node: (random.uniform(0, 10), random.uniform(0, 10)) for node in G.nodes()}\n", " nx.set_node_attributes(G, pos, 'pos')\n", "\n", " return G\n", "\n", "graph = generate_graph(20)\n", "A = nx.adjacency_matrix(graph).todense()\n", "\n", "def generate_distance_matrix(graph):\n", " distance_matrix = dict(nx.floyd_warshall(graph))\n", " num_nodes = graph.number_of_nodes()\n", " distance_array = np.zeros((num_nodes, num_nodes))\n", " for i, row in distance_matrix.items():\n", " for j, distance in row.items():\n", " \n", " distance_array[i][j] = distance\n", " return distance_array\n", "\n", "\n", "\n", "# Générer la matrice de distances\n", "distance_matrix = generate_distance_matrix(graph)\n", "\n", "# Afficher la matrice de distances\n", "print(distance_matrix)\n", "\n", "\n", "print(A)\n", "\n", "pos = nx.get_node_attributes(graph, 'pos')\n", "# Dessiner le graphe\n", "nx.draw(graph, with_labels=True)\n", "plt.show()" ] }, { "attachments": {}, "cell_type": "markdown", "id": "9aac4453", "metadata": {}, "source": [ "# ACO appliqué sur notre graphe\n" ] }, { "cell_type": "code", "execution_count": 47, "id": "301fb5e8-9804-4592-9193-5915f1b9ecad", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Meilleure solution : [0, 10, 1, 15, 13, 14, 4, 6, 19, 8, 9, 12, 5, 3, 18, 11, 16, 17, 20, 2, 7, 0]\n", "Distance totale : 22.0\n" ] } ], "source": [ "import time\n", "\n", "# Fonction d'évaluation de la qualité d'une solution (ici, la distance totale)\n", "def evaluate_solution(solution, distances):\n", " total_distance = 0\n", " num_nodes = len(solution)\n", "\n", " for i in range(num_nodes - 1):\n", " current_node = solution[i]\n", " next_node = solution[i + 1]\n", " total_distance += distances[current_node][next_node]\n", "\n", " # Ajouter la distance de retour au dépôt\n", " total_distance += distances[solution[-1]][solution[0]]\n", "\n", " return total_distance\n", "\n", "\n", "# Algorithme ACO\n", "def ant_colony_optimization(distances, num_ants, num_iterations, evaporation_rate, alpha, beta):\n", " num_nodes = len(distances)\n", " \n", " pheromone = np.ones((num_nodes, num_nodes)) # Matrice de phéromones initiale\n", " best_solution = None\n", " best_distance = float('inf')\n", "\n", " start_time = time.time()\n", "\n", "\n", " for iteration in range(num_iterations):\n", " # Construction de solutions par les fourmis\n", " solutions = []\n", "\n", " for ant in range(num_ants):\n", " visited = set()\n", " current_node = random.randint(0, num_nodes - 1)\n", " visited.add(current_node)\n", " solution = [current_node]\n", "\n", " while len(visited) < num_nodes:\n", " next_node = None\n", " probabilities = []\n", "\n", " # Calcul des probabilités de choisir chaque prochain nœud\n", " for node in range(num_nodes):\n", " if node not in visited:\n", " pheromone_value = pheromone[current_node][node]\n", " distance_value = distances[current_node][node]\n", " probability = (pheromone_value ** alpha) * ((1 / distance_value) ** beta)\n", " probabilities.append((node, probability))\n", "\n", " total_probability = sum(prob for _, prob in probabilities)\n", " probabilities = [(node, prob / total_probability) for node, prob in probabilities]\n", "\n", " # Choix du prochain nœud basé sur les probabilités\n", " roulette_wheel = random.random()\n", " probability_sum = 0\n", "\n", " for node, probability in probabilities:\n", " probability_sum += probability\n", " if probability_sum >= roulette_wheel:\n", " next_node = node\n", " break\n", "\n", " visited.add(next_node)\n", " solution.append(next_node)\n", " current_node = next_node\n", "\n", "\n", " # Ajouter le retour au dépôt central à la fin du trajet\n", " solution.append(0)\n", "\n", " solutions.append(solution)\n", "\n", " # Évaluation des solutions et mise à jour de la meilleure solution\n", " for solution in solutions:\n", " distance = evaluate_solution(solution, distances)\n", " if distance < best_distance:\n", " best_solution = solution\n", " best_distance = distance\n", "\n", " # Mise à jour des phéromones\n", " pheromone *= evaporation_rate # Évaporation des phéromones existantes\n", "\n", " for solution in solutions:\n", " delta_pheromone = 1 / evaluate_solution(solution, distances)\n", " for i in range(num_nodes - 1):\n", " node1 = solution[i]\n", " node2 = solution[i + 1]\n", " pheromone[node1][node2] += delta_pheromone\n", " pheromone[node2][node1] += delta_pheromone\n", "\n", " return best_solution, best_distance\n", "\n", "\n", " \n", "num_ants = 10\n", "num_iterations = 50\n", "evaporation_rate = 0.5\n", "alpha = 1\n", "beta = 1\n", "\n", "\n", "best_solution, best_distance = ant_colony_optimization(distance_matrix, num_ants, num_iterations, evaporation_rate, alpha, beta)\n", "\n", "\n", "\n", "print(\"Meilleure solution :\", best_solution)\n", "print(\"Distance totale :\", best_distance)\n" ] }, { "attachments": {}, "cell_type": "markdown", "id": "7e878834", "metadata": {}, "source": [ "# Tracé du chemin" ] }, { "cell_type": "code", "execution_count": 96, "id": "2a019d78", "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "x_values = [graph.nodes[x]['pos'][0] for x in best_solution]\n", "y_values = [graph.nodes[x]['pos'][1] for x in best_solution]\n", "\n", "# Création de la figure et des axes\n", "fig, ax = plt.subplots()\n", "ax.set_aspect('equal')\n", "ax.set_xlabel('Coordonnée X')\n", "ax.set_ylabel('Coordonnée Y')\n", "ax.set_title(\"Tracé du trajet emprunté par les fourmis\")\n", "\n", "# Tracer le graphe sans les arêtes\n", "nx.draw_networkx_nodes(graph, pos=nx.get_node_attributes(graph, 'pos'), ax=ax)\n", "nx.draw_networkx_labels(graph, pos=nx.get_node_attributes(graph, 'pos'), ax=ax)\n", "\n", "# Tracer uniquement le trajet emprunté par les fourmis\n", "ax.plot(x_values, y_values, linestyle='-', marker='o')\n", "\n", "# Tracer une ligne du dernier nœud au premier nœud pour fermer la boucle\n", "ax.plot([x_values[-1], x_values[0]], [y_values[-1], y_values[0]], linestyle='-', color='r')\n", "\n", "# Afficher le graphique\n", "plt.show()" ] }, { "attachments": {}, "cell_type": "markdown", "id": "9017d1eb", "metadata": {}, "source": [ "# Avec un nombre de camion disponible" ] }, { "cell_type": "code", "execution_count": 48, "id": "23e32e2a", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Meilleure solution : [[10, 1, 15, 17, 20, 7, 2, 0], [13, 14, 4, 6, 19, 8, 9, 0], [16, 11, 18, 3, 12, 5, 0, 0]]\n", "Distance totale : 21.0\n" ] } ], "source": [ "import concurrent.futures\n", "num_trucks = 3 # Nombre de camions disponibles\n", "\n", "\n", "# Fonction d'évaluation de la qualité d'une solution (ici, la distance totale)\n", "def evaluate_solution(solution, distances):\n", " total_distance = 0\n", " num_nodes = len(solution)\n", "\n", " for i in range(num_nodes - 1):\n", " current_node = solution[i]\n", " next_node = solution[i + 1]\n", " total_distance += distances[current_node][next_node]\n", "\n", "\n", " #if solution[-1] == 0 and len(solution) < num_nodes:\n", " #return float('inf')\n", "\n", " # Ajouter la distance de retour au dépôt\n", " total_distance += distances[solution[-1]][solution[0]]\n", "\n", " return total_distance\n", "\n", " \n", "def ant_colony_optimization(distances, num_ants, num_iterations, evaporation_rate, alpha, beta, num_trucks):\n", " num_nodes = len(distances)\n", " \n", " pheromone = np.ones((num_nodes, num_nodes)) # Matrice de phéromones initiale\n", " best_solution = None\n", " best_distance = float('inf')\n", "\n", " start_time = time.time()\n", "\n", " for iteration in range(num_iterations):\n", " # Construction de solutions par les fourmis\n", " solutions = []\n", "\n", " for ant in range(num_ants):\n", " visited = set()\n", " current_node = random.randint(0, num_nodes - 1)\n", " visited.add(current_node)\n", " solution = [current_node]\n", "\n", " while len(visited) < num_nodes:\n", " next_node = None\n", " probabilities = []\n", "\n", " # Calcul des probabilités de choisir chaque prochain nœud\n", " for node in range(num_nodes):\n", " if node not in visited and (node !=0 or len(visited) == num_nodes - 1):\n", " pheromone_value = pheromone[current_node][node]\n", " distance_value = distances[current_node][node]\n", " probability = (pheromone_value ** alpha) * ((1 / distance_value) ** beta)\n", " probabilities.append((node, probability))\n", "\n", " total_probability = sum(prob for _, prob in probabilities)\n", " probabilities = [(node, prob / total_probability) for node, prob in probabilities]\n", "\n", " \n", " roulette_wheel = random.random()\n", " probability_sum = 0\n", "\n", "\n", " for node, probability in probabilities:\n", " \n", " probability_sum += probability\n", " if probability_sum >= roulette_wheel:\n", " next_node = node\n", " break\n", "\n", " visited.add(next_node)\n", " solution.append(next_node)\n", " current_node = next_node\n", "\n", " # Ajouter le retour au dépôt central à la fin du trajet\n", " solution.append(0)\n", "\n", " solutions.append(solution)\n", "\n", " # Évaluation des solutions et mise à jour de la meilleure solution\n", " for solution in solutions:\n", " distance = evaluate_solution(solution, distances)\n", " if distance < best_distance:\n", " best_solution = solution\n", " best_distance = distance\n", "\n", " # Mise à jour des phéromones\n", " pheromone *= evaporation_rate # Évaporation des phéromones existantes\n", "\n", " for solution in solutions:\n", " delta_pheromone = 1 / evaluate_solution(solution, distances)\n", " for i in range(num_nodes - 1):\n", " node1 = solution[i]\n", " node2 = solution[i + 1]\n", " pheromone[node1][node2] += delta_pheromone\n", " pheromone[node2][node1] += delta_pheromone\n", "\n", " # Séparer la meilleure solution en trajets pour chaque camion\n", " truck_solutions = []\n", " num_nodes_per_truck = num_nodes // num_trucks\n", "\n", " for i in range(num_trucks):\n", " start_index = i * num_nodes_per_truck\n", " end_index = start_index + num_nodes_per_truck\n", " truck_solution = best_solution[start_index:end_index]\n", " truck_solutions.append(truck_solution + [0])\n", " \n", "\n", " return truck_solutions, best_distance\n", "\n", "\n", "def trucks_thread(i, num_nodes_per_truck, best_solution, truck_solutions):\n", " start_index = i * num_nodes_per_truck\n", " end_index = start_index + num_nodes_per_truck\n", " truck_solution = best_solution[start_index:end_index]\n", " truck_solutions.append(truck_solution)\n", " return truck_solutions\n", "\n", "\n", "\n", "num_ants = 10\n", "num_iterations = 100\n", "evaporation_rate = 0.5\n", "alpha = 1\n", "beta = 1\n", "\n", "best_truck_solutions, best_distance = ant_colony_optimization(distance_matrix, num_ants, num_iterations, evaporation_rate, alpha, beta, num_trucks)\n", "\n", "\n", "print(\"Meilleure solution :\", best_truck_solutions)\n", "print(\"Distance totale :\", best_distance)\n", " " ] }, { "cell_type": "code", "execution_count": 8, "id": "106d6902", "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Créer une liste de couleurs pour chaque véhicule\n", "colors = ['red', 'blue', 'green', 'orange', 'purple'] # Ajoutez plus de couleurs si nécessaire\n", "\n", "# Création de la figure et des axes\n", "fig, ax = plt.subplots()\n", "ax.set_aspect('equal')\n", "ax.set_xlabel('Coordonnée X')\n", "ax.set_ylabel('Coordonnée Y')\n", "ax.set_title(\"Tracé du trajet emprunté par les fourmis\")\n", "\n", "# Tracer le graphe sans les arêtes\n", "nx.draw_networkx_nodes(graph, pos=nx.get_node_attributes(graph, 'pos'), ax=ax)\n", "nx.draw_networkx_labels(graph, pos=nx.get_node_attributes(graph, 'pos'), ax=ax)\n", "\n", "# Tracer chaque trajet de chaque véhicule avec une couleur différente\n", "for i, truck_solution in enumerate(best_truck_solutions):\n", " x_values = [graph.nodes[x]['pos'][0] for x in truck_solution]\n", " y_values = [graph.nodes[x]['pos'][1] for x in truck_solution]\n", " ax.plot(x_values, y_values, linestyle='-', marker='o', color=colors[i % len(colors)])\n", "\n", " # Tracer une ligne du dernier nœud au premier nœud pour fermer la boucle\n", " ax.plot([x_values[-1], x_values[0]], [y_values[-1], y_values[0]], linestyle='-', color=colors[i % len(colors)])\n", "\n", "# Afficher le graphique\n", "plt.show()" ] }, { "attachments": {}, "cell_type": "markdown", "id": "29df0137", "metadata": {}, "source": [ "# En rajoutant la contrainte de Time Window pour une instance de VRPTW" ] }, { "cell_type": "code", "execution_count": 2, "id": "8266e414-d350-4101-8f15-9cc05ee02934", "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "20\n", "Client 0 : (0, inf)\n", "Client 1 : (19, 60)\n", "Client 2 : (71, 111)\n", "Client 3 : (51, 73)\n", "Client 4 : (96, 127)\n", "Client 5 : (88, 109)\n", "Client 6 : (69, 113)\n", "Client 7 : (24, 67)\n", "Client 8 : (19, 36)\n", "Client 9 : (82, 110)\n", "Client 10 : (43, 66)\n", "Client 11 : (42, 59)\n", "Client 12 : (65, 104)\n", "Client 13 : (79, 90)\n", "Client 14 : (53, 103)\n", "Client 15 : (60, 110)\n", "Client 16 : (65, 102)\n", "Client 17 : (63, 76)\n", "Client 18 : (28, 56)\n", "Client 19 : (27, 73)\n", "Client 20 : (41, 87)\n", "[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20]\n", "[(0, 2), (0, 1), (0, 8), (0, 15), (0, 16), (0, 18), (1, 6), (1, 3), (1, 8), (1, 17), (2, 4), (2, 13), (2, 9), (3, 8), (3, 18), (3, 13), (3, 17), (3, 19), (4, 8), (4, 14), (5, 15), (5, 9), (5, 6), (5, 11), (5, 16), (6, 9), (7, 15), (7, 17), (7, 10), (8, 10), (8, 20), (9, 19), (10, 11), (11, 13), (12, 19), (12, 16), (13, 18), (13, 20), (14, 18), (15, 16), (19, 20)]\n" ] } ], "source": [ "\n", "\n", "# 2. Attribuer les fenêtres de temps aux clients\n", "def assign_time_windows(graph):\n", " # Créer un dictionnaire pour stocker les fenêtres de temps des clients\n", " time_windows = {}\n", "\n", " # Définir la fenêtre de temps pour le dépôt central (nœud 0)\n", " time_windows[0] = (0, float('inf'))\n", "\n", " # Assigner une fenêtre de temps à chaque client\n", " for node in graph.nodes():\n", " if node !=0 and node != graph.number_of_nodes() :\n", " # Générer une fenêtre de temps aléatoire pour chaque client\n", " start_time = random.randint(0, 100)\n", " end_time = start_time + random.randint(10, 50)\n", " time_windows[node] = (start_time, end_time)\n", " \n", "\n", " return time_windows\n", "\n", "# Attribuer les fenêtres de temps aux clients\n", "time_windows = assign_time_windows(graph)\n", "\n", "print(max(graph.nodes()))\n", "# Afficher les fenêtres de temps assignées\n", "for node, window in time_windows.items():\n", " print(\"Client\", node, \":\", window)\n", " \n", "#paramètres ACO\n", "\n", "print(graph.nodes())\n", "print(graph.edges())\n", "\n" ] }, { "cell_type": "code", "execution_count": 11, "id": "901e6b93", "metadata": {}, "outputs": [], "source": [ "import concurrent.futures\n", "import random\n", "import numpy as np\n", "import time\n", "\n", "num_trucks = 3 # Nombre de camions disponibles\n", "\n", "\n", "\n", "# Fonction d'évaluation de la qualité d'une solution (ici, la distance totale)\n", "def evaluate_solution(solution, distances, time_windows):\n", " total_distance = 0\n", " total_delay = 0\n", " arrival_time = 0\n", " num_nodes = len(solution)\n", " waiting_times = []\n", "\n", " for i in range(num_nodes - 1):\n", " current_node = solution[i]\n", " next_node = solution[i + 1]\n", " total_distance += distances[current_node][next_node]\n", " arrival_time += distances[current_node][next_node]\n", "\n", " if arrival_time < time_windows[next_node][0]:\n", " waiting_time = time_windows[next_node][0] - arrival_time\n", " waiting_times.append((next_node, waiting_time))\n", " arrival_time = time_windows[next_node][0]\n", " elif arrival_time > time_windows[next_node][1]:\n", " total_delay += arrival_time - time_windows[next_node][1]\n", "\n", " # Ajouter la distance de retour au dépôt\n", " total_distance += distances[solution[-1]][solution[0]]\n", "\n", " return total_distance, total_delay, waiting_times\n", "\n", " \n", "num_ants = 10\n", "num_iterations = 100\n", "evaporation_rate = 0.5\n", "alpha = 1\n", "beta = 1\n", "\n", "def ant_colony_optimization(distances, num_ants, num_iterations, evaporation_rate, alpha, beta, num_trucks):\n", " num_nodes = len(distances)\n", " pheromone = np.ones((num_nodes, num_nodes)) \n", " best_solution = None\n", " best_distance = float('inf')\n", " best_delay = float('inf')\n", " best_score = float('inf') # Initialize the best_score\n", " best_waiting_times = None\n", "\n", " for iteration in range(num_iterations):\n", " solutions = []\n", " for ant in range(num_ants):\n", " visited = set()\n", " current_node = random.randint(0, num_nodes - 1)\n", " visited.add(current_node)\n", " solution = [current_node]\n", " while len(visited) < num_nodes:\n", " next_node = None\n", " probabilities = []\n", " arrival_time = 0\n", " for node in range(num_nodes):\n", " if node not in visited and (node !=0 or len(visited) == num_nodes - 1):\n", " pheromone_value = pheromone[current_node][node]\n", " distance_value = distances[current_node][node]\n", " wait_time = max(0, time_windows[node][0]- (arrival_time + distance_value))\n", " probability = (pheromone_value ** alpha) * ((1 / (distance_value + wait_time)) ** beta)\n", " probabilities.append((node, probability))\n", " total_probability = sum(prob for _, prob in probabilities)\n", " probabilities = [(node, prob / total_probability) for node, prob in probabilities]\n", " roulette_wheel = random.random()\n", " probability_sum = 0\n", " for node, probability in probabilities:\n", " probability_sum += probability\n", " if probability_sum >= roulette_wheel:\n", " next_node = node\n", " break\n", " visited.add(next_node)\n", " solution.append(next_node)\n", " current_node = next_node\n", " solution.append(0)\n", " solutions.append(solution)\n", "\n", " for solution in solutions:\n", " distance, delay, waiting_times = evaluate_solution(solution, distances, time_windows)\n", " score = distance + delay\n", " if score < best_score:\n", " best_solution = solution\n", " best_distance = distance\n", " best_delay = delay\n", " best_waiting_times = waiting_times\n", " pheromone *= evaporation_rate\n", " for solution in solutions:\n", " delta_pheromone = 1 / (evaluate_solution(solution, distances, time_windows)[0] + 0.01)\n", " for i in range(num_nodes - 1):\n", " node1 = solution[i]\n", " node2 = solution[i + 1]\n", " pheromone[node1][node2] += delta_pheromone\n", " pheromone[node2][node1] += delta_pheromone\n", " truck_solutions = []\n", " num_nodes_per_truck = num_nodes // num_trucks\n", " for i in range(num_trucks):\n", " start_index = i * num_nodes_per_truck\n", " end_index = start_index + num_nodes_per_truck\n", " truck_solution = best_solution[start_index:end_index]\n", " truck_solutions.append(truck_solution + [0])\n", " return truck_solutions, best_distance, best_waiting_times\n", "\n", "\n", "\n", "\n", " \n", " \n", "#best_truck_solutions, best_distance, best_waiting_times = ant_colony_optimization(distance_matrix, num_ants, num_iterations, evaporation_rate, alpha, beta, num_trucks)\n", "\n", "#print(\"Meilleure solution :\", best_truck_solutions)\n", "#print(\"Distance totale :\", best_distance)\n" ] }, { "cell_type": "code", "execution_count": 17, "id": "f24a5980", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Meilleure solution : [[15, 19, 8, 10, 2, 3, 6, 0], [16, 4, 7, 1, 20, 18, 11, 0], [9, 17, 12, 13, 5, 14, 0, 0]]\n", "Distance totale : 49.0\n", "Meilleure solution : [[10, 20, 8, 7, 18, 12, 11, 0], [1, 19, 3, 15, 13, 2, 5, 0], [17, 16, 9, 4, 14, 6, 0, 0]]\n", "Distance totale : 48.0\n", "Meilleure solution : [[12, 18, 19, 1, 8, 7, 20, 0], [2, 16, 11, 15, 6, 4, 14, 0], [10, 9, 3, 5, 13, 17, 0, 0]]\n", "Distance totale : 46.0\n", "Meilleure solution : [[6, 13, 5, 19, 8, 1, 7, 0], [14, 18, 20, 11, 2, 10, 15, 0], [3, 17, 16, 4, 9, 12, 0, 0]]\n", "Distance totale : 46.0\n" ] } ], "source": [ "num_thread = 4\n", "\n", "with concurrent.futures.ThreadPoolExecutor(max_workers=num_thread) as executor:\n", " futures = [executor.submit(ant_colony_optimization, distance_matrix, num_ants, num_iterations, evaporation_rate, alpha, beta, num_trucks) for _ in range(num_thread)]\n", "\n", " for future in concurrent.futures.as_completed(futures):\n", " best_truck_solutions, best_distance, best_waiting_times = future.result()\n", " print(\"Meilleure solution :\", best_truck_solutions)\n", " print(\"Distance totale :\", best_distance)" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.11.3" } }, "nbformat": 4, "nbformat_minor": 5 }