SzybciorSmartTraktor/genetical_algorithm.py
2022-06-08 21:16:30 +02:00

122 lines
4.8 KiB
Python

import random
from copy import copy
import settings
import tree
def evaluate_values(fuel, water, feritizer, seeds, fields_with_plants, k):
fields_to_sow = 0
fields_to_water = 0
fields_to_feritize = 0
fields_to_harvest = 0
width = settings.Field.horizontal_count()
height = settings.Field.vertical_count()
ans = 0
for i in range(width):
for j in range(height):
if fields_with_plants[i][j] == 'potato_empty' or fields_with_plants[i][j] == 'carrot_empty' or \
fields_with_plants[i][j] == 'wheat_empty':
fields_to_sow += 1
elif fields_with_plants[i][j] == 'potato_sow' or fields_with_plants[i][j] == 'carrot_sow' or \
fields_with_plants[i][j] == 'wheat_sow':
fields_to_water += 1
elif fields_with_plants[i][j] == 'potato_watered' or fields_with_plants[i][j] == 'carrot_watered' or \
fields_with_plants[i][j] == 'wheat_watered':
fields_to_feritize += 1
elif fields_with_plants[i][j] == 'potato_feritized' or fields_with_plants[i][j] == 'carrot_feritized' or \
fields_with_plants[i][j] == 'wheat_feritized':
fields_to_harvest += 1
t = tree.treelearn()
if water < fields_to_water or feritizer < fields_to_feritize or seeds < fields_to_sow or fuel < 1000:
return 5
if tree.make_decision(t, fuel, water, feritizer, 0, 0, 0, 0, 0, seeds):
return 5
if fuel > 2000:
return 0
if k == 0:
ans += (fuel) / 30 - fields_to_harvest
ans += water - fields_to_water
ans += feritizer - fields_to_feritize - fields_to_water
ans += seeds - fields_to_harvest - fields_to_sow
if k == 1:
ans += water - fields_to_water
ans += feritizer - fields_to_water - fields_to_feritize
ans += seeds - fields_to_sow
ans += (fuel - 1100) / 30 - fields_to_harvest
if k == 2:
ans += feritizer - fields_to_feritize
ans += seeds - fields_to_sow
ans += (fuel - 800) / 15 - fields_to_feritize - fields_to_harvest
ans += water - fields_to_water - fields_to_sow
if k == 3:
ans += seeds - fields_to_sow
ans += (fuel - 400) / 30 - fields_to_harvest
ans += water - fields_to_water - fields_to_sow
ans += feritizer - fields_to_feritize - fields_to_water - fields_to_sow
return ans
def fitness(solution, fields_plants, k):
fuel = solution[0]
water = solution[1]
feritizer = solution[2]
seeds = solution[3]
if fuel / 30 + water + feritizer + seeds > 200:
ans = 0
else:
ans = evaluate_values(fuel, water, feritizer, seeds, fields_plants, k)
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]