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修改超参数设置

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This commit is contained in:
weixin_46229132 2025-03-24 17:09:51 +08:00
parent 61be8ad37c
commit fe37f7ac0f
7 changed files with 150 additions and 27 deletions
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13
GA/main.py
View File

@ -14,7 +14,15 @@ best_solution = None
best_row_boundaries = None
best_col_boundaries = None
# ---------------------------
# 需要修改的超参数
# ---------------------------
R = 3
C = 3
params_file = 'params3'
with open(params_file + '.yml', 'r', encoding='utf-8') as file:
params = yaml.safe_load(file)
@ -37,13 +45,13 @@ battery_energy_capacity = params['battery_energy_capacity']
numbers = [0.0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]
# 生成所有的排列情况（取三次，每次都可以从10个数中选）
row_product = list(product(numbers, repeat=1))
row_product = list(product(numbers, repeat=R))
# 对每种情况从小到大排序，并剔除重复的情况
row_cuts_set = set(
tuple(sorted(set(item for item in prod if item > 0))) for prod in row_product)
row_cuts_set = sorted(row_cuts_set)
col_product = list(product(numbers, repeat=1))
col_product = list(product(numbers, repeat=C))
col_cuts_set = set(
tuple(sorted(set(item for item in prod if item > 0))) for prod in col_product)
col_cuts_set = sorted(col_cuts_set)
@ -95,6 +103,7 @@ print("Best solution:", best_solution)
print("Time:", best_T)
print("Row boundaries:", best_row_boundaries)
print("Col boundaries:", best_col_boundaries)
print("Car Paths:", car_paths)
output_data = {
'row_boundaries': best_row_boundaries,

15
GA/main_parallel.py
View File

@ -27,7 +27,14 @@ if __name__ == "__main__": # 重要：在 Windows 上必须加这一行
np.random.seed(42)
random.seed(42)
params_file = 'params3'
# ---------------------------
# 需要修改的超参数
# ---------------------------
R = 3
C = 1
params_file = 'params2'
batch_size = 60 # 控制一次最多并行多少个任务
with open(params_file + '.yml', 'r', encoding='utf-8') as file:
params = yaml.safe_load(file)
@ -50,13 +57,13 @@ if __name__ == "__main__": # 重要：在 Windows 上必须加这一行
numbers = [0.0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]
# 生成所有的排列情况（取三次，每次都可以从10个数中选）
row_product = list(product(numbers, repeat=1))
row_product = list(product(numbers, repeat=R))
# 对每种情况从小到大排序，并剔除重复的情况
row_cuts_set = set(
tuple(sorted(set(item for item in prod if item > 0))) for prod in row_product)
row_cuts_set = sorted(row_cuts_set)
col_product = list(product(numbers, repeat=1))
col_product = list(product(numbers, repeat=C))
col_cuts_set = set(
tuple(sorted(set(item for item in prod if item > 0))) for prod in col_product)
col_cuts_set = sorted(col_cuts_set)
@ -65,7 +72,6 @@ if __name__ == "__main__": # 重要：在 Windows 上必须加这一行
best_solution = None
best_row_boundaries = None
best_col_boundaries = None
batch_size = 60 # 控制一次最多并行多少个任务
all_tasks = [(row_cuts, col_cuts)
for row_cuts in row_cuts_set for col_cuts in col_cuts_set]
@ -123,6 +129,7 @@ if __name__ == "__main__": # 重要：在 Windows 上必须加这一行
print("Time:", best_T)
print("Row boundaries:", best_row_boundaries)
print("Col boundaries:", best_col_boundaries)
print("Car Paths:", car_paths)
output_data = {
'row_boundaries': best_row_boundaries,

12
GA/sa_finetune.py
View File

@ -203,12 +203,18 @@ def load_initial_solution(file_path):
if __name__ == "__main__":
random.seed(42)
# 从 JSON 文件加载初始解
file_path = r"e:\studio2\HPCC_code\solutions\trav_ga_params3_parallel.json"
# ---------------------------
# 需要修改的超参数
# ---------------------------
file_path = r"solutions\trav_ga_params2_parallel.json"
max_iterations=10000
initial_temp=100
cooling_rate=0.95
initial_row_cuts, initial_col_cuts, car_paths = load_initial_solution(
file_path)
sa = SA_FineTuner(initial_row_cuts, initial_col_cuts, car_paths)
sa = SA_FineTuner(initial_row_cuts, initial_col_cuts, car_paths, max_iterations, initial_temp, cooling_rate)
best_row_cuts, best_col_cuts, best_T = sa.run()
# 输出结果

22
mtkl_sovler.py
View File

@ -7,12 +7,20 @@ import numpy as np
# 固定随机种子，便于复现
random.seed(42)
num_iterations = 10000
# ---------------------------
# 参数设置
# 需要修改的超参数
# ---------------------------
params_file = 'params3'
num_iterations = 10000
# 随机生成分区的行分段数与列分段数
# R = random.randint(0, 3) # 行分段数
# C = random.randint(0, 3) # 列分段数
R = 3
C = 1
params_file = 'params2'
with open(params_file + '.yml', 'r', encoding='utf-8') as file:
params = yaml.safe_load(file)
@ -38,12 +46,6 @@ best_T = float('inf')
best_solution = None
for iteration in range(num_iterations):
# 随机生成分区的行分段数与列分段数
# R = random.randint(0, 3) # 行分段数
# C = random.randint(0, 3) # 列分段数
R = 1
C = 1
# 生成随机的行、列分割边界
horiz = [np.clip(np.floor(random.random() * 10) / 10, 0.0, 0.9)
for _ in range(R)]
@ -174,6 +176,8 @@ for iteration in range(num_iterations):
# ---------------------------
if best_solution is not None:
print("最佳 T:", best_solution['T_max'])
print("Row boundaries:", best_solution['row_boundaries'])
print("Col boundaries:", best_solution['col_boundaries'])
print("最佳路径:", best_solution['car_paths'])
# 保存分区边界和车辆轨迹到JSON文件

30
solutions/mtkl_params2.json Normal file
View File

@ -0,0 +1,30 @@
{
"row_boundaries": [
0.0,
0.3,
0.4,
0.7,
1.0
],
"col_boundaries": [
0.0,
0.5,
1.0
],
"car_paths": [
[
2,
0
],
[
4,
5,
3,
1
],
[
6,
7
]
]
}

30
solutions/trav_ga_params2_parallel.json Normal file
View File

@ -0,0 +1,30 @@
{
"row_boundaries": [
0.0,
0.2,
0.4,
0.7,
1.0
],
"col_boundaries": [
0.0,
0.5,
1.0
],
"car_paths": [
[
7,
6
],
[
4,
2,
0
],
[
1,
3,
5
]
]
}

55
visualization.py
View File

@ -2,7 +2,8 @@ import matplotlib.pyplot as plt
import matplotlib.patches as patches
import json
def visualize_solution(row_boundaries, col_boundaries, car_paths, W, H):
def visualize_solution(row_boundaries, col_boundaries, car_paths_coords, W, H):
plt.rcParams['font.family'] = ['sans-serif']
plt.rcParams['font.sans-serif'] = ['SimHei']
fig, ax = plt.subplots()
@ -28,32 +29,68 @@ def visualize_solution(row_boundaries, col_boundaries, car_paths, W, H):
for col in col_boundaries:
ax.axvline(x=col * W, color='black', linestyle='--')
# 绘制每辆车的轨迹
for system_id, path in enumerate(car_paths):
path = [(region_center[0], region_center[1])] + path + [(region_center[0], region_center[1])]
# 绘制每辆车的轨迹并标注区域序号
for system_id, path in enumerate(car_paths_coords):
path = [(region_center[0], region_center[1])] + \
path + [(region_center[0], region_center[1])]
y, x = zip(*path)
ax.plot(x, y, marker='o', color=colors[int(system_id) % len(colors)], label=f"系统 {system_id}")
ax.plot(x, y, marker='o', color=colors[int(
system_id) % len(colors)], label=f"系统 {system_id}")
# 标注每个区域的序号
for idx, (px, py) in enumerate(zip(x[1:-1], y[1:-1])): # 跳过起点和终点
ax.text(px, py, str(idx), color='black', fontsize=8, ha='center', va='center')
# 添加图例
ax.legend()
plt.show()
if __name__ == "__main__":
import yaml
# 读取参数
with open('params3.yml', 'r', encoding='utf-8') as file:
# ---------------------------
# 需要修改的超参数
# ---------------------------
params_file = 'params2'
solution_file = r'solutions\trav_ga_params2_parallel.json'
with open(params_file + '.yml', 'r', encoding='utf-8') as file:
params = yaml.safe_load(file)
H = params['H']
W = params['W']
k = params['num_cars']
# 读取最佳方案的JSON文件
with open(r'solutions\trav_ga_params3_parallel.json', 'r', encoding='utf-8') as f:
with open(solution_file, 'r', encoding='utf-8') as f:
best_solution = json.load(f)
row_boundaries = best_solution['row_boundaries']
col_boundaries = best_solution['col_boundaries']
car_paths = best_solution['car_paths']
visualize_solution(row_boundaries, col_boundaries, car_paths, W, H)
# 计算分块区域的中心点坐标
rectangle_centers = []
for i in range(len(row_boundaries) - 1):
for j in range(len(col_boundaries) - 1):
r1 = row_boundaries[i]
r2 = row_boundaries[i + 1]
c1 = col_boundaries[j]
c2 = col_boundaries[j + 1]
d = (r2 - r1) * H * (c2 - c1) * W # 任务的照片数量（矩形面积）
# 计算任务矩形中心，用于后续车辆移动时间计算
center_r = (r1 + r2) / 2.0 * H
center_c = (c1 + c2) / 2.0 * W
rectangle_centers.append((center_r, center_c))
# 将car_paths里的index换成坐标
car_paths_coords = [[] for _ in range(k)]
for car_idx in range(k):
car_path = car_paths[car_idx]
for point in car_path:
car_paths_coords[car_idx].append(rectangle_centers[point])
visualize_solution(row_boundaries, col_boundaries, car_paths_coords, W, H)