Rick van Hattem
150 lines
28 KiB
Plaintext
150 lines
28 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {
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"pycharm": {
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"name": "#%%\n"
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}
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Generation 100 2x1, 1x5, 1x10, 2x25, price: $495\n",
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"Generation 200 2x1, 1x5, 1x10, 2x25, price: $495\n",
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"Generation 300 2x1, 1x5, 1x10, 2x25, price: $495\n",
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"Generation 400 2x1, 1x5, 1x10, 2x25, price: $495\n",
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"Generation 500 2x1, 1x5, 1x10, 2x25, price: $495\n",
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"Generation 600 2x1, 1x5, 1x10, 2x25, price: $495\n",
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"Generation 700 2x1, 1x5, 1x10, 2x25, price: $495\n",
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"Generation 800 2x1, 1x5, 1x10, 2x25, price: $495\n",
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"Generation 900 2x1, 1x5, 1x10, 2x25, price: $495\n",
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"Generation 1000 2x1, 1x5, 1x10, 2x25, price: $495\n"
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]
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},
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{
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"data": {
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"image/png": 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\n",
|
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"text/plain": [
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|
"<Figure size 432x288 with 1 Axes>"
|
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]
|
|
},
|
|
"metadata": {
|
|
"needs_background": "light"
|
|
},
|
|
"output_type": "display_data"
|
|
},
|
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{
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"data": {
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"image/png": 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\n",
|
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"text/plain": [
|
|
"<Figure size 432x288 with 1 Axes>"
|
|
]
|
|
},
|
|
"execution_count": 3,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"import numpy as np\n",
|
|
"import pygad\n",
|
|
"\n",
|
|
"# Combination of number of boards with the prices per board\n",
|
|
"stack_prices = np.array(\n",
|
|
" [\n",
|
|
" [1, 10], # $10 per board\n",
|
|
" [5, 5 * 9], # $9 per board\n",
|
|
" [10, 10 * 8], # $8 per board\n",
|
|
" [25, 25 * 7], # $7 per board\n",
|
|
" ]\n",
|
|
")\n",
|
|
"\n",
|
|
"# The minimum number of boards to buy\n",
|
|
"desired_boards = 67\n",
|
|
"\n",
|
|
"\n",
|
|
"def fitness_function(solution: np.ndarray, solution_index):\n",
|
|
" # We can't have a negative number of boards\n",
|
|
" if (solution < 0).any():\n",
|
|
" return float('-inf')\n",
|
|
"\n",
|
|
" # Make sure we have the minimum number of boards required\n",
|
|
" total_area = stack_prices[:, 0] * solution\n",
|
|
" if total_area.sum() < desired_boards:\n",
|
|
" return float('-inf')\n",
|
|
"\n",
|
|
" # Calculate the price of the solution\n",
|
|
" price = stack_prices[:, 1] * solution\n",
|
|
" # The fitness function maximizes so invert the price\n",
|
|
" return - price.sum()\n",
|
|
"\n",
|
|
"\n",
|
|
"def print_status(instance):\n",
|
|
" # Only print the status every 100 iterations\n",
|
|
" if instance.generations_completed % 100:\n",
|
|
" return\n",
|
|
"\n",
|
|
" total = 0\n",
|
|
" solution = instance.best_solution()[0]\n",
|
|
" # Print the generation, bulk size and the total price\n",
|
|
" print(f'Generation {instance.generations_completed}', end=' ')\n",
|
|
" for mp, (boards, price) in zip(solution, stack_prices):\n",
|
|
" print(f'{mp:2d}x{boards},', end='')\n",
|
|
" total += mp * price\n",
|
|
" print(f' price: ${total}')\n",
|
|
"\n",
|
|
"\n",
|
|
"ga_instance = pygad.GA(\n",
|
|
" num_generations=1000,\n",
|
|
" num_parents_mating=10,\n",
|
|
" # Every generation will have 100 solutions\n",
|
|
" sol_per_pop=100,\n",
|
|
" # We use 1 gene per stack size\n",
|
|
" num_genes=stack_prices.shape[0],\n",
|
|
" fitness_func=fitness_function,\n",
|
|
" on_generation=print_status,\n",
|
|
" # We can't buy half a board, so use integers\n",
|
|
" gene_type=int,\n",
|
|
" # Limit the solution space to our maximum number of boards\n",
|
|
" gene_space=np.arange(desired_boards),\n",
|
|
" # Limit how large the change in a mutation can be\n",
|
|
" random_mutation_min_val=-2,\n",
|
|
" random_mutation_max_val=2,\n",
|
|
" # Disable crossover since it does not make sense in this case\n",
|
|
" crossover_probability=0,\n",
|
|
" # Set the number of genes that are allowed to mutate at once\n",
|
|
" mutation_num_genes=stack_prices.shape[0] // 2,\n",
|
|
")\n",
|
|
"\n",
|
|
"ga_instance.run()\n",
|
|
"ga_instance.plot_fitness()\n"
|
|
]
|
|
}
|
|
],
|
|
"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": "3.9.12"
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 1
|
|
}
|