forked from Vizards8/DQN_Mine
-
Notifications
You must be signed in to change notification settings - Fork 0
/
scheduling_env.py
225 lines (195 loc) · 8.75 KB
/
scheduling_env.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
from random import random, uniform, randint
from agent import DQN
from hparam import hparams as hp
import numpy as np
class job:
def __init__(self, last_arrival, id):
self.id = id
self.T_arrival = round(last_arrival + uniform(0, 1), 2) # 到达时间
self.T_deadline = round(self.T_arrival + uniform(3, 5), 2) # 截止
self.type = randint(0, hp.type_num - 1) # 任务类别
self.mask = np.ones(hp.action_dim) # mask
self.action = None # 选择的机器
self.T_spent = None # 耗时
self.T_start = None # 开始时间
self.priority = 2 # 优先度
def reset(self):
self.action = None
self.T_spent = None
self.T_start = None
self.priority = 2
class machine:
def __init__(self, id):
self.id = id
self.spent = [] # list:每个type在这个机器上运行的时间
self.running = None
def reset(self):
self.running = None
class SchedulingEnv:
def __init__(self, job_num, machine_num, type_num):
self.job_num = job_num
self.machine_num = machine_num # 机器个数
self.type_num = type_num # 任务type个数
self.machines = [machine(i) for i in range(self.machine_num)]
self.jobs = []
self.waiting = [] # 一个waiting_list
def reset(self):
for i in self.jobs:
i.reset()
for i in self.machines:
i.reset()
self.waiting = []
def re_random_job(self):
# 重新随机job
self.jobs = []
# 随机第一个job
data = job(0, 0)
for j in self.machines:
if j.spent[data.type] == -1:
data.mask[j.id] = 0
self.jobs.append(data)
# 随机剩余的job
for i in range(1, self.job_num):
data = job(self.jobs[-1].T_arrival, i)
for j in self.machines:
if j.spent[data.type] == -1:
data.mask[j.id] = 0
self.jobs.append(data)
# 初始化数据
def init(self):
print('Initializing data...')
self.reset()
# # 随机每个machine不同type的service时间
# re_random = True # True:要重新随机
# while re_random:
# for i in self.machines:
# # 防止一台机器什么任务也做不了
# machine_flag = True
# while machine_flag:
# i.spent = []
# for j in range(self.type_num):
# if random() > 0.5: # 随机数判断在这个机器上能不能做该任务
# i.spent.append(uniform(2.5, 5.5))
# else:
# i.spent.append(-1)
# for k in i.spent:
# if not k == -1:
# machine_flag = False
# print('machine_id:', i.id, i.spent)
# # 防止一个任务什么机器都做不了
# for ii in range(self.type_num):
# print('我执行了吗')
# pass_id = False
# for jj in self.machines:
# if not jj.spent[ii] == -1:
# pass_id = True
# break
# if not pass_id:
# re_random = False
# break
# 随机每个machine不同type的service时间
if self.type_num == 10 and self.machine_num == 30:
self.machines[0].spent = [-1, -1, -1, -1, -1, 4.1, 1.8, 1.4, 3.4, -1]
self.machines[1].spent = [-1, -1, -1, -1, -1, 2.9, -1, 1.6, -1, 3.9]
self.machines[2].spent = [-1, 4.8, -1, 3.4, -1, -1, -1, -1, -1, 4.7]
self.machines[3].spent = [-1, -1, -1, -1, -1, 1.4, 2.4, 1.0, 1.6, -1]
self.machines[4].spent = [1.2, 3.3, -1, -1, 3.1, 2.3, -1, -1, -1, -1]
self.machines[5].spent = [4.2, 1.8, -1, -1, 3.3, 1.1, -1, -1, -1, -1]
self.machines[6].spent = [4.0, 1.0, -1, -1, 4.6, 4.2, -1, -1, -1, -1]
self.machines[7].spent = [4.9, 2.7, 4.2, 2.2, -1, -1, -1, -1, -1, -1]
self.machines[8].spent = [-1, -1, -1, -1, -1, 1.5, 4.3, 4.8, 4.9, -1]
self.machines[9].spent = [2.6, 4.3, -1, -1, 1.8, 5.0, -1, -1, -1, -1]
self.machines[10].spent = [-1, -1, -1, -1, -1, -1, -1, 4.8, 4.1, 3.6]
self.machines[11].spent = [-1, -1, -1, -1, -1, 1.8, -1, 2.6, -1, 4.6]
self.machines[12].spent = [-1, -1, -1, -1, -1, 2.1, -1, 2.4, -1, 3.7]
self.machines[13].spent = [-1, -1, -1, 3.0, -1, 3.7, -1, -1, -1, 2.8]
self.machines[14].spent = [-1, 2.2, -1, 3.1, -1, -1, -1, -1, -1, 3.3]
self.machines[15].spent = [-1, -1, -1, -1, -1, 4.6, -1, 3.7, -1, 3.2]
self.machines[16].spent = [4.5, 1.4, 4.2, 1.5, -1, -1, -1, -1, -1, -1]
self.machines[17].spent = [4.8, -1, 1.1, -1, 2.3, -1, -1, -1, -1, -1]
self.machines[18].spent = [2.0, 3.0, 2.2, 1.1, -1, -1, -1, -1, -1, -1]
self.machines[19].spent = [-1, -1, -1, -1, -1, 2.1, 1.9, 4.3, 3.0, -1]
self.machines[20].spent = [-1, -1, -1, -1, -1, -1, -1, 1.9, 3.6, 3.8]
self.machines[21].spent = [2.2, -1, 3.3, -1, 3.6, -1, -1, -1, -1, -1]
self.machines[22].spent = [-1, -1, -1, 4.3, -1, 4.0, -1, -1, -1, 3.4]
self.machines[23].spent = [-1, -1, -1, -1, -1, -1, -1, 2.3, 4.6, 1.2]
self.machines[24].spent = [3.9, -1, 1.1, -1, 4.2, -1, -1, -1, -1, -1]
self.machines[25].spent = [-1, -1, -1, 2.2, -1, 1.9, -1, -1, -1, 1.8]
self.machines[26].spent = [-1, 2.0, -1, 3.8, -1, -1, -1, -1, -1, 1.6]
self.machines[27].spent = [-1, -1, -1, -1, -1, -1, -1, 4.4, 2.4, 4.3]
self.machines[28].spent = [2.8, -1, 2.4, -1, 1.7, -1, -1, -1, -1, -1]
self.machines[29].spent = [2.2, 4.0, 1.3, 4.9, -1, -1, -1, -1, -1, -1]
for i in self.machines:
print('machine_id:', i.id, i.spent)
else:
for i in self.machines:
i.spent = []
for j in range(self.type_num):
if random() > 0.4: # 随机数判断在这个机器上能不能做该任务
i.spent.append(uniform(2.5, 5.5))
else:
i.spent.append(-1)
print('machine_id:', i.id, i.spent)
# 随机job
self.re_random_job()
def get_state(self, job, T):
# state = [T - job.T_arrival, # t_suspended
# job.priority,
# len(self.waiting) # list.number
# ]
state = [job.priority]
for i in self.machines:
# t_spent
# state.append(i.spent[job.type])
# t_balance
# state.append(job.T_deadline - T - i.spent[job.type])
# t_total_balance
if i.running:
state.append(job.T_deadline - i.spent[job.type] - i.running.T_start - i.running.T_spent)
else:
state.append(job.T_deadline - T - i.spent[job.type])
# machine_time_let:机器上正在做的任务的剩余时间
# if i.running:
# state.append(i.running.T_start + i.running.T_spent - T)
# else:
# state.append(0)
# machine_balance:机器上正在做的任务如果完成了的时间结余
# if i.running:
# state.append(i.running.T_deadline - T - i.spent[i.running.type])
# else:
# state.append(0)
return state
# feasible 如果没有bug，都是True
def step(self, action, job, T):
reward = 0
feasible = True
# 添加进waiting_list
if action >= self.machine_num:
job.priority = (action - 5) / (hp.action_dim - self.machine_num - 1)
self.waiting.append(job)
# reward -= max(0, T - 150)
else:
# 所需执行时间是负数
if self.machines[action].spent[job.type] < 0:
reward += -0.001
feasible = False
# 机器的剩余任务时间是正
if self.machines[action].running:
reward += -0.001
feasible = False
# 可行，安排进机器
if reward == 0:
job.T_start = T
job.T_spent = self.machines[action].spent[job.type]
self.machines[action].running = job
reward = job.T_deadline - T - job.T_spent
# 记录action
job.action = action
# print(f'reward: {reward}')
return reward, feasible
# # For the test
# machines = [[] for i in range(5)]
# print(machines)
# data = pd.read_excel('./data.xlsx')
# for i in data:
# print(i)