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fedden/dfo_fly_competition.ipynb

Created November 21, 2017 14:57
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dfo_fly_competition.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"import numpy as np\n",
"np.set_printoptions(precision=3, suppress=True)"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"scrolled": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"attempt 0\n",
" * fly solution: [ 7 8 10 2 9 3 5 4 6 1]\n",
" * difference sum: 0\n",
" * difference product: 0\n",
"\n",
"attempt 1\n",
" * fly solution: [10 9 8 7 2 1 5 4 6 3]\n",
" * difference sum: 0\n",
" * difference product: 0\n",
"\n",
"attempt 2\n",
" * fly solution: [ 8 7 9 10 2 3 5 1 6 4]\n",
" * difference sum: 0\n",
" * difference product: 0\n",
"\n",
"attempt 3\n",
" * fly solution: [ 2 9 8 7 10 1 5 3 6 4]\n",
" * difference sum: 0\n",
" * difference product: 0\n",
"\n",
"attempt 4\n",
" * fly solution: [ 7 10 8 2 9 3 1 6 4 5]\n",
" * difference sum: 0\n",
" * difference product: 0\n",
"\n",
"attempt 5\n",
" * fly solution: [ 9 7 8 10 2 4 3 6 1 5]\n",
" * difference sum: 0\n",
" * difference product: 0\n",
"\n",
"attempt 6\n",
" * fly solution: [ 7 8 9 10 2 6 5 4 3 1]\n",
" * difference sum: 0\n",
" * difference product: 0\n",
"\n",
"attempt 7\n",
" * fly solution: [10 2 8 9 7 5 3 6 4 1]\n",
" * difference sum: 0\n",
" * difference product: 0\n",
"\n",
"attempt 8\n",
" * fly solution: [ 2 10 8 7 9 5 6 4 3 1]\n",
" * difference sum: 0\n",
" * difference product: 0\n",
"\n",
"attempt 9\n",
" * fly solution: [ 7 2 9 10 8 4 5 6 3 1]\n",
" * difference sum: 0\n",
" * difference product: 0\n",
"\n",
"attempt 10\n",
" * fly solution: [ 9 8 10 2 7 1 6 3 5 4]\n",
" * difference sum: 0\n",
" * difference product: 0\n",
"\n",
"attempt 11\n",
" * fly solution: [10 7 9 8 2 4 3 5 1 6]\n",
" * difference sum: 0\n",
" * difference product: 0\n",
"\n",
"attempt 12\n",
" * fly solution: [10 2 8 7 9 4 1 6 5 3]\n",
" * difference sum: 0\n",
" * difference product: 0\n",
"\n",
"attempt 13\n",
" * fly solution: [ 8 7 10 9 2 5 4 1 6 3]\n",
" * difference sum: 0\n",
" * difference product: 0\n",
"\n",
"attempt 14\n",
" * fly solution: [ 7 8 10 9 2 6 5 1 3 4]\n",
" * difference sum: 0\n",
" * difference product: 0\n",
"\n",
"attempt 15\n",
" * fly solution: [ 9 7 10 2 8 3 6 1 4 5]\n",
" * difference sum: 0\n",
" * difference product: 0\n",
"\n",
"attempt 16\n",
" * fly solution: [ 9 8 7 10 2 3 6 4 1 5]\n",
" * difference sum: 0\n",
" * difference product: 0\n",
"\n",
"attempt 17\n",
" * fly solution: [ 9 7 8 10 2 6 5 4 1 3]\n",
" * difference sum: 0\n",
" * difference product: 0\n",
"\n",
"attempt 18\n",
" * fly solution: [10 7 9 2 8 1 3 6 5 4]\n",
" * difference sum: 0\n",
" * difference product: 0\n",
"\n",
"attempt 19\n",
" * fly solution: [ 9 7 10 8 2 1 5 3 6 4]\n",
" * difference sum: 0\n",
" * difference product: 0\n",
"\n",
"attempt 20\n",
" * fly solution: [ 9 2 7 8 10 5 6 4 1 3]\n",
" * difference sum: 0\n",
" * difference product: 0\n",
"\n",
"attempt 21\n",
" * fly solution: [ 9 7 10 8 2 3 5 6 4 1]\n",
" * difference sum: 0\n",
" * difference product: 0\n",
"\n",
"attempt 22\n",
" * fly solution: [ 9 10 7 8 2 4 3 6 1 5]\n",
" * difference sum: 0\n",
" * difference product: 0\n",
"\n",
"attempt 23\n",
" * fly solution: [10 8 9 2 7 4 5 1 3 6]\n",
" * difference sum: 0\n",
" * difference product: 0\n",
"\n",
"attempt 24\n",
" * fly solution: [ 8 2 7 10 9 6 3 5 1 4]\n",
" * difference sum: 0\n",
" * difference product: 0\n",
"\n",
"attempt 25\n",
" * fly solution: [10 8 7 9 2 5 4 1 6 3]\n",
" * difference sum: 0\n",
" * difference product: 0\n",
"\n",
"attempt 26\n",
" * fly solution: [ 7 8 9 2 10 1 3 5 4 6]\n",
" * difference sum: 0\n",
" * difference product: 0\n",
"\n",
"attempt 27\n",
" * fly solution: [ 9 2 10 8 7 4 5 6 3 1]\n",
" * difference sum: 0\n",
" * difference product: 0\n",
"\n",
"attempt 28\n",
" * fly solution: [ 2 7 8 10 9 1 6 4 3 5]\n",
" * difference sum: 0\n",
" * difference product: 0\n",
"\n",
"attempt 29\n",
" * fly solution: [ 8 10 9 7 2 5 3 1 6 4]\n",
" * difference sum: 0\n",
" * difference product: 0\n",
"\n",
"attempt 30\n",
" * fly solution: [ 8 2 10 7 9 1 4 3 6 5]\n",
" * difference sum: 0\n",
" * difference product: 0\n",
"\n",
"attempt 31\n",
" * fly solution: [ 7 2 9 10 8 5 4 6 1 3]\n",
" * difference sum: 0\n",
" * difference product: 0\n",
"\n",
"attempt 32\n",
" * fly solution: [ 8 7 10 9 2 1 4 3 6 5]\n",
" * difference sum: 0\n",
" * difference product: 0\n",
"\n",
"attempt 33\n",
" * fly solution: [ 7 10 8 2 9 6 4 3 5 1]\n",
" * difference sum: 0\n",
" * difference product: 0\n",
"\n",
"attempt 34\n",
" * fly solution: [ 7 9 10 8 2 3 5 1 6 4]\n",
" * difference sum: 0\n",
" * difference product: 0\n",
"\n",
"attempt 35\n",
" * fly solution: [ 7 2 10 9 8 3 1 4 6 5]\n",
" * difference sum: 0\n",
" * difference product: 0\n",
"\n",
"attempt 36\n",
" * fly solution: [10 7 2 8 9 5 3 6 1 4]\n",
" * difference sum: 0\n",
" * difference product: 0\n",
"\n",
"attempt 37\n",
" * fly solution: [ 7 9 8 10 2 6 5 1 3 4]\n",
" * difference sum: 0\n",
" * difference product: 0\n",
"\n",
"attempt 38\n",
" * fly solution: [ 7 9 10 2 8 3 5 6 4 1]\n",
" * difference sum: 0\n",
" * difference product: 0\n",
"\n",
"attempt 39\n",
" * fly solution: [ 2 9 10 8 7 4 5 6 1 3]\n",
" * difference sum: 0\n",
" * difference product: 0\n",
"\n",
"attempt 40\n",
" * fly solution: [10 8 7 2 9 4 5 6 3 1]\n",
" * difference sum: 0\n",
" * difference product: 0\n",
"\n",
"attempt 41\n",
" * fly solution: [ 9 8 2 10 7 4 5 6 3 1]\n",
" * difference sum: 0\n",
" * difference product: 0\n",
"\n",
"attempt 42\n",
" * fly solution: [ 8 9 2 7 10 6 1 5 3 4]\n",
" * difference sum: 0\n",
" * difference product: 0\n",
"\n",
"attempt 43\n",
" * fly solution: [ 8 9 10 7 2 6 3 5 4 1]\n",
" * difference sum: 0\n",
" * difference product: 0\n",
"\n",
"attempt 44\n",
" * fly solution: [ 9 10 2 8 7 5 4 3 1 6]\n",
" * difference sum: 0\n",
" * difference product: 0\n",
"\n",
"attempt 45\n",
" * fly solution: [ 7 10 2 9 8 6 3 5 4 1]\n",
" * difference sum: 0\n",
" * difference product: 0\n",
"\n",
"attempt 46\n",
" * fly solution: [ 7 2 9 8 10 4 5 6 1 3]\n",
" * difference sum: 0\n",
" * difference product: 0\n",
"\n",
"attempt 47\n",
" * fly solution: [ 9 2 7 10 8 5 4 1 6 3]\n",
" * difference sum: 0\n",
" * difference product: 0\n",
"\n",
"attempt 48\n",
" * fly solution: [ 2 10 8 7 9 3 1 4 6 5]\n",
" * difference sum: 0\n",
" * difference product: 0\n",
"\n",
"attempt 49\n",
" * fly solution: [ 7 8 9 2 10 6 1 3 5 4]\n",
" * difference sum: 0\n",
" * difference product: 0\n"
]
}
],
"source": [
"def create_random_population(size):\n",
" return np.random.random((size, 10))\n",
"\n",
"\n",
"def get_fitness(fly):\n",
" '''Less is better'''\n",
" fly_sorted_indices = np.argsort(fly)\n",
" fly_solution = fly_sorted_indices + 1\n",
" \n",
" assert np.sum(fly_solution) == 55\n",
" assert len(np.unique(fly_solution)) == 10\n",
" \n",
" difference_one = abs(36 - np.sum(fly_solution[:5]))\n",
" difference_two = abs(360 - np.product(fly_solution[-5:]))\n",
" return difference_one + difference_two\n",
"\n",
"\n",
"for iteration in range(50):\n",
" size = 100\n",
" disturbance_threshold = 0.01\n",
"\n",
" lower = -1.0\n",
" upper = 1.0\n",
" iteration_amount = 100\n",
"\n",
" population = create_random_population(size)\n",
"\n",
" all_time_best = None\n",
" all_time_best_score = np.finfo(np.float32).max\n",
"\n",
" best_neighbour = np.zeros_like(population[0])\n",
"\n",
" done = False\n",
"\n",
" while not done:\n",
"\n",
" fitnesses = np.array([get_fitness(p) for p in population])\n",
"\n",
" swarms_best_index = np.argmin(fitnesses)\n",
" swarms_best = population[swarms_best_index]\n",
"\n",
" if np.amin(fitnesses) < all_time_best_score:\n",
" all_time_best_score = np.amin(fitnesses)\n",
" all_time_best = swarms_best\n",
"\n",
" if all_time_best_score == 0:\n",
" done = True\n",
" break\n",
"\n",
" r = np.random.uniform(0.0, 1.0, population.shape)\n",
"\n",
" for i, p in enumerate(population):\n",
" left = (i - 1) if i is not 0 else len(population) - 1\n",
" right = (i + 1) if i is not (len(population) - 1) else 0\n",
"\n",
" best_neighbour = population[left] if fitnesses[left] < fitnesses[right] else population[right]\n",
"\n",
" for x in range(len(p)):\n",
" if r[i][x] < disturbance_threshold:\n",
" p[x] = np.random.uniform(lower, upper)\n",
" else:\n",
" update = swarms_best[x] - best_neighbour[x]\n",
" p[x] = best_neighbour[x] + np.random.uniform(0.0, 1.0) * update\n",
"\n",
"\n",
" solution = np.argsort(all_time_best) + 1\n",
" print('\\nattempt', iteration)\n",
" print(' * fly solution: ', solution)\n",
" print(' * difference sum: ', abs(36 - np.sum(solution[:5])))\n",
" print(' * difference product: ', abs(360 - np.product(solution[-5:])))\n"
]
}
],
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"language": "python",
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