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+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "Using TensorFlow backend.\n"
+ ]
+ }
+ ],
+ "source": [
+ "import csv\n",
+ "import math\n",
+ "import random\n",
+ "import sys\n",
+ "from scipy.spatial import distance\n",
+ "import pandas as pd\n",
+ "from numpy import * \n",
+ "import numpy as np\n",
+ "import matplotlib.pyplot as plt\n",
+ "import math\n",
+ "import csv\n",
+ "import random\n",
+ "import time\n",
+ "import sys\n",
+ "import datetime\n",
+ "import timeit\n",
+ "from sklearn.neighbors import DistanceMetric\n",
+ "from math import radians,cos,sin\n",
+ "from haversine import haversine, Unit\n",
+ "from scipy.spatial import distance\n",
+ "from sklearn.preprocessing import MinMaxScaler\n",
+ "from keras.models import Sequential\n",
+ "from keras.layers import Bidirectional, GlobalMaxPool1D\n",
+ "from keras.layers import LSTM\n",
+ "from keras.layers import Dropout, Dense\n",
+ "from math import sqrt\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "#Load dataset sebelum integrasi\n",
+ "Data1 = pd.read_csv('./tri/Data Toba Samosir - Sheet3.csv')\n",
+ "Data1.drop(Data1.filter(regex=\"Unname\"),axis=1, inplace=True)\n",
+ "Data2 = pd.read_csv('./tri/Data Toba Samosir - Sheet1.csv')\n",
+ "Data2.drop(Data2.filter(regex=\"Unname\"),axis=1, inplace=True)\n",
+ "Data3 = pd.read_csv('./tri/List_city.csv')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "<div>\n",
+ "<style scoped>\n",
+ " .dataframe tbody tr th:only-of-type {\n",
+ " vertical-align: middle;\n",
+ " }\n",
+ "\n",
+ " .dataframe tbody tr th {\n",
+ " vertical-align: top;\n",
+ " }\n",
+ "\n",
+ " .dataframe thead th {\n",
+ " text-align: right;\n",
+ " }\n",
+ "</style>\n",
+ "<table border=\"1\" class=\"dataframe\">\n",
+ " <thead>\n",
+ " <tr style=\"text-align: right;\">\n",
+ " <th></th>\n",
+ " <th>ID_City</th>\n",
+ " <th>City</th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " <tr>\n",
+ " <th>0</th>\n",
+ " <td>0</td>\n",
+ " <td>Pantai BUL BUL</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>1</th>\n",
+ " <td>1</td>\n",
+ " <td>BUKIT travel Gibeon</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>2</th>\n",
+ " <td>2</td>\n",
+ " <td>Pakkodian</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>3</th>\n",
+ " <td>3</td>\n",
+ " <td>Taman Eden 100 Tobasa</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>4</th>\n",
+ " <td>4</td>\n",
+ " <td>Water Park Tambunan</td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ "</table>\n",
+ "</div>"
+ ],
+ "text/plain": [
+ " ID_City City\n",
+ "0 0 Pantai BUL BUL\n",
+ "1 1 BUKIT travel Gibeon\n",
+ "2 2 Pakkodian\n",
+ "3 3 Taman Eden 100 Tobasa\n",
+ "4 4 Water Park Tambunan"
+ ]
+ },
+ "execution_count": 3,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "Data3.head()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "start = datetime.datetime.strptime(\"21-07-2020\", \"%d-%m-%Y\")\n",
+ "end = datetime.datetime.strptime(\"22-07-2020\", \"%d-%m-%Y\")\n",
+ "date_generated = [start + datetime.timedelta(days=x) for x in range(0, (end-start).days)]\n",
+ "#print(len(date_generated))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "#cost = input()\n",
+ "cost = 400000\n",
+ "Cost = int(cost)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Random Data"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 28,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "209.0"
+ ]
+ },
+ "execution_count": 28,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "def getting_distance(Data):\n",
+ " distance_route = []\n",
+ " last_distance = 0\n",
+ " distance = 0\n",
+ " for i in range(0,len(Data)-1):\n",
+ " source = Data[i]\n",
+ " target = Data[i+1]\n",
+ " distance_route.append(Data2.iloc[source][target])\n",
+ " for i in range(0,len(Data)-1):\n",
+ " source = Data[len(Data)-1]\n",
+ " target = Data[len(Data)-len(Data)]\n",
+ " last_distance = Data2.iloc[source][target] \n",
+ " distance = sum(distance_route)+last_distance\n",
+ " return distance\n",
+ "\n",
+ "\n",
+ "id_city = list(Data3['ID_City'])\n",
+ "Data4 = random.sample(range(len(id_city)), 7)\n",
+ "getting_distance(Data4)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 29,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "[30, 0, 16, 32, 20, 29, 1]"
+ ]
+ },
+ "execution_count": 29,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "Data4"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 30,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "class Fitness_value:\n",
+ " def getting_max_distance():\n",
+ " max_distance = 0 \n",
+ " max_distance += len(date_generated) * 720\n",
+ " return max_distance\n",
+ " def getting_max_cost():\n",
+ " max_cost = 0\n",
+ " max_cost +=Cost\n",
+ " return max_cost"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 31,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "720"
+ ]
+ },
+ "execution_count": 31,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "Fitness_value.getting_max_distance()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 32,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "class Bee:\n",
+ " def __init__(self, node_set):\n",
+ " self.role = ''\n",
+ " self.path = list(node_set) # stores all nodes in each bee, will randomize foragers\n",
+ " self.distance = 0\n",
+ " self.temperature = 0\n",
+ " self.cycle = 0 \n",
+ " self.cost = 0"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 33,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def initialize_hive(population, data):\n",
+ " path = Data4\n",
+ " hive = [Bee(path) for i in range (0, population)]\n",
+ " return hive"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 34,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def assign_roles(hive, role_percentiles):\n",
+ " forager_percent = 0.5\n",
+ " onlooker_percent = 0.5\n",
+ " role_percent = [onlooker_percent, forager_percent]\n",
+ " scout_percent = 0.2\n",
+ " population = len(hive)\n",
+ " onlooker_count = math.floor(population * role_percentiles[0])\n",
+ " forager_count = math.floor(population * role_percentiles[1])\n",
+ " for i in range(0, onlooker_count):\n",
+ " hive[i].role = 'O'\n",
+ " for i in range(onlooker_count, (onlooker_count + forager_count)):\n",
+ " hive[i].role = 'F'\n",
+ " random.shuffle(hive[i].path)\n",
+ " hive[i].distance = getting_distance(hive[i].path)\n",
+ " return hive"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 35,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def mutate_path(path):\n",
+ " # - will go out of range if last element is chosen.\n",
+ " path = Data4\n",
+ " new_path = random.sample(path,len(path))\n",
+ " return new_path"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 36,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def forage(bee,limit):\n",
+ " new_path = mutate_path(bee.path)\n",
+ " new_distance = getting_distance(new_path)\n",
+ " if new_distance < bee.distance:\n",
+ " bee.path = new_path\n",
+ " bee.distance = new_distance\n",
+ " bee.cycle = 0 # reset cycle so bee can continue to make progress\n",
+ " else:\n",
+ " bee.cycle += 1\n",
+ " if bee.cycle >= limit: # if bee is not making progress\n",
+ " bee.role = 'S'\n",
+ " return bee.distance, list(bee.path)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 37,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def scout(bee):\n",
+ " new_path = list(bee.path)\n",
+ " random.shuffle(new_path)\n",
+ " bee.path = new_path\n",
+ " bee.distance = getting_distance(bee.path)\n",
+ " # bee.temperature = Weather\n",
+ " bee.role = 'F'\n",
+ " bee.cycle = 0"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 38,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def waggle(hive, best_distance,forager_limit, scout_count):\n",
+ " best_path = []\n",
+ " results = []\n",
+ " for i in range(0, len(hive)):\n",
+ " if hive[i].role == 'F':\n",
+ " distance, path = forage(hive[i], forager_limit)\n",
+ " if distance < best_distance:\n",
+ " best_distance = distance\n",
+ " best_path = list(hive[i].path)\n",
+ " results.append((i, distance))\n",
+ "\n",
+ " elif hive[i].role == 'S':\n",
+ " scout(hive[i])\n",
+ " # after processing all bees, set worst performers to scout\n",
+ " results.sort(reverse = True, key=lambda tup: tup[1])\n",
+ " scouts = [ tup[0] for tup in results[0:int(scout_count)] ]\n",
+ " for new_scout in scouts:\n",
+ " hive[new_scout].role = 'S'\n",
+ " return best_distance, best_path"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 39,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def recruit(hive, best_distance, best_path):\n",
+ " for i in range(0, len(hive)):\n",
+ " if hive[i].role == 'O':\n",
+ " new_path = mutate_path(best_path)\n",
+ " new_distance = getting_distance(new_path)\n",
+ " if new_distance < best_distance:\n",
+ " best_distance = new_distance\n",
+ " best_path = new_path\n",
+ " return best_distance, best_path"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 40,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def print_details(cycle, path, distance,bee):\n",
+ " \"\"\"\n",
+ " Prints cycle details to console.\n",
+ " \"\"\"\n",
+ " print(\"CYCLE: {}\".format(cycle))\n",
+ " print(\"PATH: {}\".format(path))\n",
+ " print(\"DISTANCE: {}\".format(distance))\n",
+ " # print(\"COST: {}\".format(cost))\n",
+ " # print(\"TEMPERATURE: {}\".format(temperature))\n",
+ " print(\"BEE: {}\".format(bee))\n",
+ " print(\"\\n\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 41,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "Maximum_distance = Fitness_value.getting_max_distance()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 42,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def main():\n",
+ " # Control parameters\n",
+ " population = 40\n",
+ " forager_percent = 0.5\n",
+ " onlooker_percent = 0.4\n",
+ " role_percent = [onlooker_percent, forager_percent]\n",
+ " scout_percent = 0.01\n",
+ " scout_count = math.ceil(population * scout_percent)\n",
+ " forager_limit = 500\n",
+ " cycle_limit = 100\n",
+ " cycle = 1\n",
+ " # temperature = Weather\n",
+ " # Data source\n",
+ " # data = read_data_from_csv(\"data/data_10.csv\")\n",
+ " # data = read_data_from_csv(\"data/data_11.csv\")\n",
+ " data = Data4\n",
+ " # Global vars\n",
+ " best_distance = sys.maxsize\n",
+ " best_path = []\n",
+ " result = ()\n",
+ " # Initialization\n",
+ " hive = initialize_hive(population, data)\n",
+ " assign_roles(hive, role_percent)\n",
+ "# cost = get_total_cost(path)\n",
+ " while cycle < cycle_limit:\n",
+ " waggle_distance,waggle_path = waggle(hive, best_distance,forager_limit,scout_count)\n",
+ " if (waggle_distance < best_distance) and (waggle_distance <= Maximum_distance):\n",
+ " best_distance = waggle_distance\n",
+ " best_path = list(waggle_path)\n",
+ " # cost = get_total_cost(path)\n",
+ " # temperature = Weather\n",
+ " print_details(cycle, best_path, best_distance,'F')\n",
+ " result = (cycle, best_path, best_distance,'F')\n",
+ " recruit_distance,recruit_path = recruit(hive, best_distance,best_path)\n",
+ " if (recruit_distance < best_distance) and (recruit_distance <= Maximum_distance):\n",
+ " best_path = list(recruit_path)\n",
+ " best_distance = recruit_distance \n",
+ "# cost = get_total_cost(path)\n",
+ " print_details(cycle, best_path, best_distance,'R')\n",
+ " result = (cycle, best_path, best_distance,'R')\n",
+ " if cycle % 100 == 0:\n",
+ " print(\"CYCLE #: {}\\n\".format(cycle))\n",
+ " cycle += 1"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 43,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "CYCLE: 1\n",
+ "PATH: [20, 1, 32, 30, 29, 0, 16]\n",
+ "DISTANCE: 191.70000000000002\n",
+ "BEE: F\n",
+ "\n",
+ "\n",
+ "CYCLE: 1\n",
+ "PATH: [30, 16, 20, 0, 29, 1, 32]\n",
+ "DISTANCE: 185.30000000000004\n",
+ "BEE: R\n",
+ "\n",
+ "\n",
+ "CYCLE: 2\n",
+ "PATH: [16, 20, 0, 1, 29, 32, 30]\n",
+ "DISTANCE: 185.20000000000002\n",
+ "BEE: F\n",
+ "\n",
+ "\n",
+ "CYCLE: 2\n",
+ "PATH: [30, 1, 29, 0, 20, 16, 32]\n",
+ "DISTANCE: 185.10000000000002\n",
+ "BEE: R\n",
+ "\n",
+ "\n",
+ "CYCLE: 3\n",
+ "PATH: [30, 32, 1, 29, 20, 16, 0]\n",
+ "DISTANCE: 185.0\n",
+ "BEE: R\n",
+ "\n",
+ "\n",
+ "CYCLE: 15\n",
+ "PATH: [32, 30, 29, 1, 16, 20, 0]\n",
+ "DISTANCE: 184.99999999999997\n",
+ "BEE: R\n",
+ "\n",
+ "\n",
+ "CYCLE: 1\n",
+ "PATH: [29, 20, 16, 0, 30, 32, 1]\n",
+ "DISTANCE: 185.0\n",
+ "BEE: F\n",
+ "\n",
+ "\n",
+ "CYCLE: 3\n",
+ "PATH: [30, 1, 29, 16, 20, 0, 32]\n",
+ "DISTANCE: 184.99999999999997\n",
+ "BEE: F\n",
+ "\n",
+ "\n",
+ "CYCLE: 1\n",
+ "PATH: [1, 29, 20, 16, 0, 32, 30]\n",
+ "DISTANCE: 184.99999999999997\n",
+ "BEE: F\n",
+ "\n",
+ "\n",
+ "CYCLE: 1\n",
+ "PATH: [32, 30, 0, 20, 16, 1, 29]\n",
+ "DISTANCE: 185.3\n",
+ "BEE: F\n",
+ "\n",
+ "\n",
+ "CYCLE: 1\n",
+ "PATH: [20, 0, 32, 30, 29, 1, 16]\n",
+ "DISTANCE: 185.0\n",
+ "BEE: R\n",
+ "\n",
+ "\n",
+ "CYCLE: 4\n",
+ "PATH: [30, 29, 1, 16, 20, 0, 32]\n",
+ "DISTANCE: 184.99999999999997\n",
+ "BEE: F\n",
+ "\n",
+ "\n",
+ "CYCLE: 1\n",
+ "PATH: [20, 16, 0, 1, 29, 30, 32]\n",
+ "DISTANCE: 185.4\n",
+ "BEE: F\n",
+ "\n",
+ "\n",
+ "CYCLE: 1\n",
+ "PATH: [0, 20, 16, 32, 30, 1, 29]\n",
+ "DISTANCE: 185.1\n",
+ "BEE: R\n",
+ "\n",
+ "\n",
+ "CYCLE: 5\n",
+ "PATH: [20, 0, 32, 30, 29, 1, 16]\n",
+ "DISTANCE: 185.0\n",
+ "BEE: R\n",
+ "\n",
+ "\n",
+ "CYCLE: 6\n",
+ "PATH: [0, 30, 32, 1, 29, 20, 16]\n",
+ "DISTANCE: 184.99999999999997\n",
+ "BEE: R\n",
+ "\n",
+ "\n",
+ "CYCLE: 1\n",
+ "PATH: [1, 0, 20, 16, 30, 32, 29]\n",
+ "DISTANCE: 185.2\n",
+ "BEE: F\n",
+ "\n",
+ "\n",
+ "CYCLE: 2\n",
+ "PATH: [30, 32, 1, 29, 0, 20, 16]\n",
+ "DISTANCE: 185.1\n",
+ "BEE: F\n",
+ "\n",
+ "\n",
+ "CYCLE: 3\n",
+ "PATH: [29, 1, 16, 20, 0, 32, 30]\n",
+ "DISTANCE: 185.0\n",
+ "BEE: R\n",
+ "\n",
+ "\n",
+ "CYCLE: 12\n",
+ "PATH: [32, 30, 29, 1, 16, 20, 0]\n",
+ "DISTANCE: 184.99999999999997\n",
+ "BEE: R\n",
+ "\n",
+ "\n",
+ "CYCLE: 1\n",
+ "PATH: [29, 1, 16, 20, 0, 32, 30]\n",
+ "DISTANCE: 185.0\n",
+ "BEE: F\n",
+ "\n",
+ "\n",
+ "CYCLE: 4\n",
+ "PATH: [0, 30, 32, 1, 29, 20, 16]\n",
+ "DISTANCE: 184.99999999999997\n",
+ "BEE: R\n",
+ "\n",
+ "\n",
+ "CYCLE: 1\n",
+ "PATH: [1, 16, 20, 0, 32, 30, 29]\n",
+ "DISTANCE: 185.0\n",
+ "BEE: F\n",
+ "\n",
+ "\n",
+ "CYCLE: 2\n",
+ "PATH: [0, 30, 32, 1, 29, 20, 16]\n",
+ "DISTANCE: 184.99999999999997\n",
+ "BEE: R\n",
+ "\n",
+ "\n",
+ "CYCLE: 1\n",
+ "PATH: [20, 0, 1, 29, 30, 32, 16]\n",
+ "DISTANCE: 185.4\n",
+ "BEE: F\n",
+ "\n",
+ "\n",
+ "CYCLE: 2\n",
+ "PATH: [32, 30, 1, 29, 0, 20, 16]\n",
+ "DISTANCE: 185.10000000000002\n",
+ "BEE: F\n",
+ "\n",
+ "\n",
+ "CYCLE: 2\n",
+ "PATH: [29, 1, 0, 16, 20, 32, 30]\n",
+ "DISTANCE: 185.00000000000003\n",
+ "BEE: R\n",
+ "\n",
+ "\n",
+ "CYCLE: 5\n",
+ "PATH: [0, 32, 30, 29, 1, 16, 20]\n",
+ "DISTANCE: 185.0\n",
+ "BEE: F\n",
+ "\n",
+ "\n",
+ "CYCLE: 21\n",
+ "PATH: [1, 29, 20, 16, 0, 32, 30]\n",
+ "DISTANCE: 184.99999999999997\n",
+ "BEE: F\n",
+ "\n",
+ "\n",
+ "CYCLE: 1\n",
+ "PATH: [20, 16, 0, 32, 30, 29, 1]\n",
+ "DISTANCE: 185.10000000000002\n",
+ "BEE: F\n",
+ "\n",
+ "\n",
+ "CYCLE: 4\n",
+ "PATH: [1, 29, 0, 16, 20, 30, 32]\n",
+ "DISTANCE: 185.0\n",
+ "BEE: R\n",
+ "\n",
+ "\n",
+ "CYCLE: 21\n",
+ "PATH: [0, 32, 30, 1, 29, 20, 16]\n",
+ "DISTANCE: 184.99999999999997\n",
+ "BEE: R\n",
+ "\n",
+ "\n",
+ "CYCLE: 1\n",
+ "PATH: [0, 30, 32, 1, 29, 20, 16]\n",
+ "DISTANCE: 184.99999999999997\n",
+ "BEE: F\n",
+ "\n",
+ "\n",
+ "CYCLE: 1\n",
+ "PATH: [16, 0, 1, 29, 30, 32, 20]\n",
+ "DISTANCE: 185.4\n",
+ "BEE: F\n",
+ "\n",
+ "\n",
+ "CYCLE: 2\n",
+ "PATH: [32, 1, 29, 0, 20, 16, 30]\n",
+ "DISTANCE: 185.1\n",
+ "BEE: F\n",
+ "\n",
+ "\n",
+ "CYCLE: 3\n",
+ "PATH: [32, 1, 29, 20, 16, 0, 30]\n",
+ "DISTANCE: 184.99999999999997\n",
+ "BEE: F\n",
+ "\n",
+ "\n",
+ "CYCLE: 1\n",
+ "PATH: [30, 32, 1, 29, 20, 16, 0]\n",
+ "DISTANCE: 185.0\n",
+ "BEE: F\n",
+ "\n",
+ "\n",
+ "CYCLE: 6\n",
+ "PATH: [30, 32, 1, 29, 16, 20, 0]\n",
+ "DISTANCE: 184.99999999999997\n",
+ "BEE: R\n",
+ "\n",
+ "\n",
+ "CYCLE: 1\n",
+ "PATH: [32, 1, 29, 0, 20, 16, 30]\n",
+ "DISTANCE: 185.1\n",
+ "BEE: F\n",
+ "\n",
+ "\n",
+ "CYCLE: 4\n",
+ "PATH: [16, 20, 32, 30, 29, 1, 0]\n",
+ "DISTANCE: 185.0\n",
+ "BEE: F\n",
+ "\n",
+ "\n",
+ "CYCLE: 34\n",
+ "PATH: [32, 30, 1, 29, 20, 16, 0]\n",
+ "DISTANCE: 184.99999999999997\n",
+ "BEE: F\n",
+ "\n",
+ "\n",
+ "CYCLE: 1\n",
+ "PATH: [32, 30, 20, 16, 0, 1, 29]\n",
+ "DISTANCE: 185.3\n",
+ "BEE: F\n",
+ "\n",
+ "\n",
+ "CYCLE: 1\n",
+ "PATH: [30, 32, 1, 29, 0, 20, 16]\n",
+ "DISTANCE: 185.1\n",
+ "BEE: R\n",
+ "\n",
+ "\n",
+ "CYCLE: 4\n",
+ "PATH: [29, 20, 16, 0, 30, 32, 1]\n",
+ "DISTANCE: 185.0\n",
+ "BEE: R\n",
+ "\n",
+ "\n",
+ "CYCLE: 61\n",
+ "PATH: [30, 29, 1, 16, 20, 0, 32]\n",
+ "DISTANCE: 184.99999999999997\n",
+ "BEE: F\n",
+ "\n",
+ "\n",
+ "CYCLE: 1\n",
+ "PATH: [0, 30, 1, 29, 32, 16, 20]\n",
+ "DISTANCE: 190.4\n",
+ "BEE: F\n",
+ "\n",
+ "\n",
+ "CYCLE: 4\n",
+ "PATH: [32, 29, 1, 0, 16, 20, 30]\n",
+ "DISTANCE: 185.10000000000002\n",
+ "BEE: F\n",
+ "\n",
+ "\n",
+ "CYCLE: 4\n",
+ "PATH: [30, 32, 1, 29, 20, 16, 0]\n",
+ "DISTANCE: 185.0\n",
+ "BEE: R\n",
+ "\n",
+ "\n",
+ "CYCLE: 72\n",
+ "PATH: [30, 32, 1, 29, 16, 20, 0]\n",
+ "DISTANCE: 184.99999999999997\n",
+ "BEE: F\n",
+ "\n",
+ "\n",
+ "CYCLE: 1\n",
+ "PATH: [20, 30, 32, 1, 29, 0, 16]\n",
+ "DISTANCE: 185.0\n",
+ "BEE: F\n",
+ "\n",
+ "\n",
+ "CYCLE: 11\n",
+ "PATH: [30, 32, 1, 29, 16, 20, 0]\n",
+ "DISTANCE: 184.99999999999997\n",
+ "BEE: F\n",
+ "\n",
+ "\n",
+ "CYCLE: 1\n",
+ "PATH: [1, 29, 0, 20, 16, 32, 30]\n",
+ "DISTANCE: 185.1\n",
+ "BEE: F\n",
+ "\n",
+ "\n",
+ "CYCLE: 3\n",
+ "PATH: [20, 32, 30, 29, 1, 0, 16]\n",
+ "DISTANCE: 185.0\n",
+ "BEE: R\n",
+ "\n",
+ "\n",
+ "CYCLE: 7\n",
+ "PATH: [32, 30, 29, 1, 16, 20, 0]\n",
+ "DISTANCE: 184.99999999999997\n",
+ "BEE: R\n",
+ "\n",
+ "\n",
+ "CYCLE: 1\n",
+ "PATH: [29, 32, 30, 16, 20, 0, 1]\n",
+ "DISTANCE: 185.20000000000002\n",
+ "BEE: F\n",
+ "\n",
+ "\n",
+ "CYCLE: 2\n",
+ "PATH: [16, 20, 30, 32, 29, 1, 0]\n",
+ "DISTANCE: 185.1\n",
+ "BEE: F\n",
+ "\n",
+ "\n",
+ "CYCLE: 4\n",
+ "PATH: [0, 16, 20, 30, 32, 1, 29]\n",
+ "DISTANCE: 185.0\n",
+ "BEE: R\n",
+ "\n",
+ "\n",
+ "CYCLE: 19\n",
+ "PATH: [1, 29, 20, 16, 0, 32, 30]\n",
+ "DISTANCE: 184.99999999999997\n",
+ "BEE: R\n",
+ "\n",
+ "\n",
+ "CYCLE: 1\n",
+ "PATH: [16, 32, 29, 1, 30, 0, 20]\n",
+ "DISTANCE: 190.5\n",
+ "BEE: F\n",
+ "\n",
+ "\n",
+ "CYCLE: 1\n",
+ "PATH: [29, 1, 30, 32, 0, 20, 16]\n",
+ "DISTANCE: 185.60000000000002\n",
+ "BEE: R\n",
+ "\n",
+ "\n",
+ "CYCLE: 2\n",
+ "PATH: [30, 0, 16, 20, 1, 29, 32]\n",
+ "DISTANCE: 185.20000000000002\n",
+ "BEE: F\n",
+ "\n",
+ "\n",
+ "CYCLE: 2\n",
+ "PATH: [32, 30, 29, 1, 20, 16, 0]\n",
+ "DISTANCE: 185.1\n",
+ "BEE: R\n",
+ "\n",
+ "\n",
+ "CYCLE: 4\n",
+ "PATH: [20, 0, 32, 30, 29, 1, 16]\n",
+ "DISTANCE: 185.0\n",
+ "BEE: F\n",
+ "\n",
+ "\n",
+ "CYCLE: 6\n",
+ "PATH: [0, 32, 30, 1, 29, 20, 16]\n",
+ "DISTANCE: 184.99999999999997\n",
+ "BEE: F\n",
+ "\n",
+ "\n"
+ ]
+ }
+ ],
+ "source": [
+ "if __name__ == '__main__':\n",
+ " for i in range (0, 20):\n",
+ " \n",
+ " main()\n",
+ "\n",
+ " # main()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def getting_best_path():\n",
+ " # Control parameters\n",
+ " population = 40\n",
+ " forager_percent = 0.5\n",
+ " onlooker_percent = 0.4\n",
+ " role_percent = [onlooker_percent, forager_percent]\n",
+ " scout_percent = 0.01\n",
+ " scout_count = math.ceil(population * scout_percent)\n",
+ " forager_limit = 500\n",
+ " cycle_limit = 100\n",
+ " cycle = 1\n",
+ " best_distance = sys.maxsize\n",
+ " best_path = []\n",
+ " result = ()\n",
+ " data = Data4\n",
+ " # Initialization\n",
+ " hive = initialize_hive(population, data)\n",
+ " assign_roles(hive, role_percent)\n",
+ " #cost = get_total_cost(path)\n",
+ " waggle_distance,waggle_path = waggle(hive, best_distance,forager_limit,scout_count)\n",
+ " if (waggle_distance < best_distance) and (waggle_distance <= Maximum_distance):\n",
+ " best_distance = waggle_distance\n",
+ " best_path = list(waggle_path)\n",
+ " recruit_distance,recruit_path = recruit(hive, best_distance,best_path)\n",
+ " if (recruit_distance < best_distance) and (recruit_distance <= Maximum_distance):\n",
+ " best_path = list(recruit_path)\n",
+ " best_distance = recruit_distance \n",
+ " return best_path"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "best_path = getting_best_path()\n",
+ "best_path"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3",
+ "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": "3.7.3"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}