a-f大等级是3级
a-c建筑每升1级分别需要8天
d-f建筑每升1级分别需要10天
目前以下建筑队列正在从0级升至1级
建筑A升级需要7天05:16:20
建筑b升级需要06:06:54
建筑c升级需要00:37:00
建筑d升级需要01:51:01
建筑e升级需要09:07:10
建筑f升级需要07:10:10
每30分钟会产生一个随机时间的升级加速包:15,30,45,60,120分钟
基于python计算,每一次随机产生的加速包,用于加速哪一个队列,做出决策优先加速哪一个建筑,最快完成建筑升级。
import random
class Building:
def __init__(self, name, building_type, initial_remaining):
self.name = name
self.type = building_type
self.level = 0 # 当前等级
self.stage_remaining = initial_remaining # 当前阶段剩余时间(秒)
self.upgrading = initial_remaining > 0 # 是否正在升级
def apply_accelerator(self, accelerator_seconds):
if not self.upgrading or self.level >= 3:
return
# 应用加速
self.stage_remaining -= accelerator_seconds
if self.stage_remaining <= 0:
self.level += 1
if self.level >= 3:
self.upgrading = False
self.stage_remaining = 0
else:
# 开始下一阶段的升级
if self.type == 'abc':
self.stage_remaining = 8 * 86400 # 8天
else:
self.stage_remaining = 10 * 86400 # 10天
self.upgrading = True
else:
self.upgrading = True
def get_total_remaining_time(self):
if self.level >= 3:
return 0
total = self.stage_remaining
remaining_stages = 3 - (self.level + 1)
if remaining_stages <= 0:
return total
if self.type == 'abc':
total += remaining_stages * 8 * 86400
else:
total += remaining_stages * 10 * 86400
return total
# 初始化建筑队列(时间转换为秒)
buildings = [
Building('A', 'abc', 7 * 86400 + 5 * 3600 + 16 * 60 + 20), # 7天05:16:20
Building('B', 'abc', 6 * 86400 + 6 * 3600 + 6 * 60 + 54), # 6天06:06:54
Building('C', 'abc', 37 * 60), # 00:37:00
Building('D', 'def', 1 * 86400 + 51 * 60 + 1), # 01:51:01
Building('E', 'def', 9 * 86400 + 7 * 3600 + 10 * 60), # 09:07:10
Building('F', 'def', 7 * 86400 + 10 * 3600 + 10 * 60 + 10), # 07:10:10
]
def select_best_target(accelerator_seconds, buildings):
min_max_time = float('inf')
best_building = None
current_totals = [b.get_total_remaining_time() for b in buildings]
current_max = max(current_totals)
if current_max == 0:
return None, 0
for b in buildings:
if not b.upgrading:
continue
# 保存当前状态
original_level = b.level
original_stage = b.stage_remaining
original_upgrading = b.upgrading
# 模拟应用加速
temp_b = Building(b.name, b.type, original_stage)
temp_b.level = original_level
temp_b.upgrading = original_upgrading
temp_b.apply_accelerator(accelerator_seconds)
# 计算新总时间
simulated_totals = []
for bb in buildings:
if bb.name == b.name:
simulated_totals.append(temp_b.get_total_remaining_time())
else:
simulated_totals.append(bb.get_total_remaining_time())
new_max = max(simulated_totals)
# 比较最优
if new_max < min_max_time or (new_max == min_max_time and best_building is None):
min_max_time = new_max
best_building = b
elif new_max == min_max_time:
if b.get_total_remaining_time() > best_building.get_total_remaining_time():
best_building = b
return best_building, min_max_time
# 模拟加速包生成和使用
while True:
# 随机生成加速包(15/30/45/60/120分钟)
accelerator = random.choice([15, 30, 45, 60, 120]) * 60 # 转换为秒
best_building, new_max = select_best_target(accelerator, buildings)
if not best_building:
print("所有建筑已升级完成!")
break
# 应用加速包
best_building.apply_accelerator(accelerator)
print(
f"使用 {accelerator // 60}分钟加速包到建筑 {best_building.name},当前最长剩余时间:{new_max // 86400}天 {new_max % 86400 // 3600}小时{(new_max % 3600) // 60}分")
# 检查是否全部完成
if all(b.get_total_remaining_time() == 0 for b in buildings):
print("全部建筑升级完成!")
break