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Genetical algorithm

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This commit is contained in:
jbiesek 2022-06-08 21:16:30 +02:00
parent 87d29f24e0
commit de1ce36aed
1 changed files with 59 additions and 1 deletions
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genetical_algorithm.py
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@ -1,3 +1,8 @@
import random
from copy import copy
import settings
import tree
def evaluate_values(fuel, water, feritizer, seeds, fields_with_plants, k): def evaluate_values(fuel, water, feritizer, seeds, fields_with_plants, k):
fields_to_sow = 0 fields_to_sow = 0
@ -61,3 +66,56 @@ def fitness(solution, fields_plants, k):
ans = evaluate_values(fuel, water, feritizer, seeds, fields_plants, k) ans = evaluate_values(fuel, water, feritizer, seeds, fields_plants, k)
return ans return ans
def solution(fields_with_plants, l):
solutions = []
ranked_solutions = []
for i in range(10000):
solution = []
fuel = random.randint(0, 2000)
water = random.randint(0, 100)
feritizer = random.randint(0, 100)
seeds = random.randint(0, 100)
solution.append(fuel)
solution.append(water)
solution.append(feritizer)
solution.append(seeds)
solutions.append(solution)
for s in solutions:
ranked_solutions.append((fitness(s, fields_with_plants, l), s))
ranked_solutions.sort()
ranked_solutions.reverse()
best_solutions = ranked_solutions[:100]
k = 1
print("Gen 1 best solution: " + str(ranked_solutions[0]))
for q in range(4):
k += 1
random_cross = random.randint(0, 3)
random_mutation_place = random.randint(0, 3)
random_mutation = random.randint(1, 5)
ranked_solutions = []
solutions = []
solutions.append(best_solutions[0][1])
for i in range(100):
for j in range(100):
if i == j:
continue
random_mutation_chance = random.randint(1, 100)
solution = copy(best_solutions[i][1])
solution[random_cross:4] = best_solutions[j][1][random_cross:4]
if random_mutation_chance <= 3:
if random_mutation_place == 0:
solution[random_mutation_place] = solution[random_mutation_place] + random_mutation * 30
else:
solution[random_mutation_place] = solution[random_mutation_place] + random_mutation
solutions.append(copy(solution))
for s in solutions:
ranked_solutions.append((fitness(s, fields_with_plants, l), s))
ranked_solutions.sort()
ranked_solutions.reverse()
best_solutions = ranked_solutions[:100]
print("Gen " + str(k) + " best solution: " + str(ranked_solutions[0]))
return ranked_solutions[0][1][0], ranked_solutions[0][1][1], ranked_solutions[0][1][2], ranked_solutions[0][1][3]