CVRP_log.ipynb

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        "!pip install ortools"
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            "Requirement already satisfied: pandas>=2.0.0 in /usr/local/lib/python3.10/dist-packages (from ortools) (2.2.2)\n",
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            "Requirement already satisfied: immutabledict>=3.0.0 in /usr/local/lib/python3.10/dist-packages (from ortools) (4.2.1)\n",
            "Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.10/dist-packages (from pandas>=2.0.0->ortools) (2.8.2)\n",
            "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.10/dist-packages (from pandas>=2.0.0->ortools) (2024.2)\n",
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      "source": [
        "\"\"\"Capacited Vehicles Routing Problem (CVRP).\"\"\"\n",
        "import pandas as pd\n",
        "from ortools.constraint_solver import routing_enums_pb2\n",
        "from ortools.constraint_solver import pywrapcp\n",
        "\n",
        "\n",
        "def create_data_model():\n",
        "    \"\"\"Stores the data for the problem.\"\"\"\n",
        "    data = {}\n",
        "    data[\"distance_matrix\"] = [\n",
        "        # fmt: off\n",
        "      [0, 548, 776, 696, 582, 274, 502, 194, 308, 194, 536, 502, 388, 354, 468, 776, 662],\n",
        "      [548, 0, 684, 308, 194, 502, 730, 354, 696, 742, 1084, 594, 480, 674, 1016, 868, 1210],\n",
        "      [776, 684, 0, 992, 878, 502, 274, 810, 468, 742, 400, 1278, 1164, 1130, 788, 1552, 754],\n",
        "      [696, 308, 992, 0, 114, 650, 878, 502, 844, 890, 1232, 514, 628, 822, 1164, 560, 1358],\n",
        "      [582, 194, 878, 114, 0, 536, 764, 388, 730, 776, 1118, 400, 514, 708, 1050, 674, 1244],\n",
        "      [274, 502, 502, 650, 536, 0, 228, 308, 194, 240, 582, 776, 662, 628, 514, 1050, 708],\n",
        "      [502, 730, 274, 878, 764, 228, 0, 536, 194, 468, 354, 1004, 890, 856, 514, 1278, 480],\n",
        "      [194, 354, 810, 502, 388, 308, 536, 0, 342, 388, 730, 468, 354, 320, 662, 742, 856],\n",
        "      [308, 696, 468, 844, 730, 194, 194, 342, 0, 274, 388, 810, 696, 662, 320, 1084, 514],\n",
        "      [194, 742, 742, 890, 776, 240, 468, 388, 274, 0, 342, 536, 422, 388, 274, 810, 468],\n",
        "      [536, 1084, 400, 1232, 1118, 582, 354, 730, 388, 342, 0, 878, 764, 730, 388, 1152, 354],\n",
        "      [502, 594, 1278, 514, 400, 776, 1004, 468, 810, 536, 878, 0, 114, 308, 650, 274, 844],\n",
        "      [388, 480, 1164, 628, 514, 662, 890, 354, 696, 422, 764, 114, 0, 194, 536, 388, 730],\n",
        "      [354, 674, 1130, 822, 708, 628, 856, 320, 662, 388, 730, 308, 194, 0, 342, 422, 536],\n",
        "      [468, 1016, 788, 1164, 1050, 514, 514, 662, 320, 274, 388, 650, 536, 342, 0, 764, 194],\n",
        "      [776, 868, 1552, 560, 674, 1050, 1278, 742, 1084, 810, 1152, 274, 388, 422, 764, 0, 798],\n",
        "      [662, 1210, 754, 1358, 1244, 708, 480, 856, 514, 468, 354, 844, 730, 536, 194, 798, 0],\n",
        "        # fmt: on\n",
        "    ]\n",
        "    data[\"demands\"] = [0, 1, 1, 2, 4, 2, 4, 8, 8, 1, 2, 1, 2, 4, 4, 8, 8]\n",
        "    data[\"vehicle_capacities\"] = [15, 15, 15, 15]\n",
        "    data[\"num_vehicles\"] = 4\n",
        "    data[\"depot\"] = 0\n",
        "    return data\n",
        "\n",
        "\n",
        "def print_solution(data, manager, routing, solution):\n",
        "    \"\"\"Prints solution on console.\"\"\"\n",
        "    print(f\"Objective: {solution.ObjectiveValue()}\")\n",
        "    total_distance = 0\n",
        "    total_load = 0\n",
        "    dic_route = {}\n",
        "    df = pd.DataFrame(columns=['route'])\n",
        "    for vehicle_id in range(data[\"num_vehicles\"]):\n",
        "        dic_route[vehicle_id] = []\n",
        "        index = routing.Start(vehicle_id)\n",
        "        plan_output = f\"Route for vehicle {vehicle_id}:\\n\"\n",
        "        route_distance = 0\n",
        "        route_load = 0\n",
        "        while not routing.IsEnd(index):\n",
        "            node_index = manager.IndexToNode(index)\n",
        "            route_load += data[\"demands\"][node_index]\n",
        "            plan_output += f\" {node_index} Load({route_load}) -> \"\n",
        "            dic_route[vehicle_id].append(node_index)\n",
        "            previous_index = index\n",
        "            index = solution.Value(routing.NextVar(index))\n",
        "            route_distance += routing.GetArcCostForVehicle(\n",
        "                previous_index, index, vehicle_id\n",
        "            )\n",
        "        plan_output += f\" {manager.IndexToNode(index)} Load({route_load})\\n\"\n",
        "        plan_output += f\"Distance of the route: {route_distance}m\\n\"\n",
        "        plan_output += f\"Load of the route: {route_load}\\n\"\n",
        "        dic_route[vehicle_id].append(manager.IndexToNode(index))\n",
        "        total_distance += route_distance\n",
        "        total_load += route_load\n",
        "    print(f\"Total distance of all routes: {total_distance}m\")\n",
        "    print(f\"Total load of all routes: {total_load}\")\n",
        "    for id,L in dic_route.items():\n",
        "      df.loc[id,'route'] = L\n",
        "    return df\n",
        "\n",
        "\n",
        "\n",
        "def main():\n",
        "    \"\"\"Solve the CVRP problem.\"\"\"\n",
        "    # Instantiate the data problem.\n",
        "    data = create_data_model()\n",
        "\n",
        "    # Create the routing index manager.\n",
        "    manager = pywrapcp.RoutingIndexManager(\n",
        "        len(data[\"distance_matrix\"]), data[\"num_vehicles\"], data[\"depot\"]\n",
        "    )\n",
        "\n",
        "    # Create Routing Model.\n",
        "    routing = pywrapcp.RoutingModel(manager)\n",
        "\n",
        "    # Create and register a transit callback.\n",
        "    def distance_callback(from_index, to_index):\n",
        "        \"\"\"Returns the distance between the two nodes.\"\"\"\n",
        "        # Convert from routing variable Index to distance matrix NodeIndex.\n",
        "        from_node = manager.IndexToNode(from_index)\n",
        "        to_node = manager.IndexToNode(to_index)\n",
        "        return data[\"distance_matrix\"][from_node][to_node]\n",
        "\n",
        "    transit_callback_index = routing.RegisterTransitCallback(distance_callback)\n",
        "\n",
        "    # Define cost of each arc.\n",
        "    routing.SetArcCostEvaluatorOfAllVehicles(transit_callback_index)\n",
        "\n",
        "    # Add Capacity constraint.\n",
        "    def demand_callback(from_index):\n",
        "        \"\"\"Returns the demand of the node.\"\"\"\n",
        "        # Convert from routing variable Index to demands NodeIndex.\n",
        "        from_node = manager.IndexToNode(from_index)\n",
        "        return data[\"demands\"][from_node]\n",
        "\n",
        "    demand_callback_index = routing.RegisterUnaryTransitCallback(demand_callback)\n",
        "    routing.AddDimensionWithVehicleCapacity(\n",
        "        demand_callback_index,\n",
        "        0,  # null capacity slack\n",
        "        data[\"vehicle_capacities\"],  # vehicle maximum capacities\n",
        "        True,  # start cumul to zero\n",
        "        \"Capacity\",\n",
        "    )\n",
        "\n",
        "    # Setting first solution heuristic.\n",
        "    search_parameters = pywrapcp.DefaultRoutingSearchParameters()\n",
        "    search_parameters.first_solution_strategy = (\n",
        "        routing_enums_pb2.FirstSolutionStrategy.PATH_CHEAPEST_ARC\n",
        "    )\n",
        "    search_parameters.local_search_metaheuristic = (\n",
        "        routing_enums_pb2.LocalSearchMetaheuristic.GUIDED_LOCAL_SEARCH\n",
        "    )\n",
        "    search_parameters.time_limit.FromSeconds(1)\n",
        "\n",
        "    # Solve the problem.\n",
        "    solution = routing.SolveWithParameters(search_parameters)\n",
        "\n",
        "    # Print solution on console.\n",
        "    if solution:\n",
        "        df = print_solution(data, manager, routing, solution)\n",
        "        return df\n",
        "\n",
        "\n",
        "if __name__ == \"__main__\":\n",
        "    out_df = main()"
      ],
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        "id": "rG6EYATiooh_",
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      "execution_count": 27,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Objective: 6208\n",
            "Total distance of all routes: 6208m\n",
            "Total load of all routes: 60\n"
          ]
        }
      ]
    },
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              "0      [0, 4, 3, 1, 7, 0]\n",
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              "        document.querySelector('#df-b51cbfe6-1880-423f-b257-9ed867e14902 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
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              "\n",
              "  <div id=\"id_e1c10045-d5bc-4807-a3be-1a890b2b3b5e\">\n",
              "    <style>\n",
              "      .colab-df-generate {\n",
              "        background-color: #E8F0FE;\n",
              "        border: none;\n",
              "        border-radius: 50%;\n",
              "        cursor: pointer;\n",
              "        display: none;\n",
              "        fill: #1967D2;\n",
              "        height: 32px;\n",
              "        padding: 0 0 0 0;\n",
              "        width: 32px;\n",
              "      }\n",
              "\n",
              "      .colab-df-generate:hover {\n",
              "        background-color: #E2EBFA;\n",
              "        box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "        fill: #174EA6;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate {\n",
              "        background-color: #3B4455;\n",
              "        fill: #D2E3FC;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate:hover {\n",
              "        background-color: #434B5C;\n",
              "        box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "        filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "        fill: #FFFFFF;\n",
              "      }\n",
              "    </style>\n",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('out_df')\"\n",
              "            title=\"Generate code using this dataframe.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M7,19H8.4L18.45,9,17,7.55,7,17.6ZM5,21V16.75L18.45,3.32a2,2,0,0,1,2.83,0l1.4,1.43a1.91,1.91,0,0,1,.58,1.4,1.91,1.91,0,0,1-.58,1.4L9.25,21ZM18.45,9,17,7.55Zm-12,3A5.31,5.31,0,0,0,4.9,8.1,5.31,5.31,0,0,0,1,6.5,5.31,5.31,0,0,0,4.9,4.9,5.31,5.31,0,0,0,6.5,1,5.31,5.31,0,0,0,8.1,4.9,5.31,5.31,0,0,0,12,6.5,5.46,5.46,0,0,0,6.5,12Z\"/>\n",
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              "    </button>\n",
              "    <script>\n",
              "      (() => {\n",
              "      const buttonEl =\n",
              "        document.querySelector('#id_e1c10045-d5bc-4807-a3be-1a890b2b3b5e button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('out_df');\n",
              "      }\n",
              "      })();\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "out_df",
              "summary": "{\n  \"name\": \"out_df\",\n  \"rows\": 4,\n  \"fields\": [\n    {\n      \"column\": \"route\",\n      \"properties\": {\n        \"dtype\": \"object\",\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 28
        }
      ]
    }
  ]
}