data[(1, 'process')] = 'Sink'
# Simulation Modeling
env = simpy.Environment()
model = {} # process_dict
process_time = {"Process1": [5.0]} # server에 할당할 process time
# Monitor
filepath = './result/event_log_DD1_1.csv'
Monitor = Monitor(filepath)
Source = Source(env, 'Source', data, model, Monitor)
for i in range(len(process_list) + 1):
if i == len(process_list):
model['Sink'] = Sink(env, 'Sink', Monitor)
else:
model['Process{0}'.format(i + 1)] = Process(env,
'Process{0}'.format(i + 1),
server_num,
model,
Monitor,
process_time=process_time)
start_sim = time.time()
env.run(until=run_time)
finish_sim = time.time()
print('#' * 80)
print("Results of simulation")
print('#' * 80)
tp_num = 100
for i in range(tp_num):
tp_info["TP_{0}".format(i + 1)] = {
"capa": 100,
"v_loaded": 0.5,
"v_unloaded": 1.0
}
Resource = Resource(env,
model,
Monitor,
tp_info=tp_info,
network=network_dist)
for i in range(len(process_list) + 1):
if i == len(process_list):
model['Sink'] = Sink(env, Monitor)
else:
model[process_list[i]] = Process(env,
process_list[i],
server_num[i],
model,
Monitor,
resource=Resource,
network=network_dist,
transporter=True)
else:
for i in range(len(process_list) + 1):
if i == len(process_list):
model['Sink'] = Sink(env, Monitor)
else:
model[process_list[i]] = Process(env, process_list[i],
save_graph = True
if save_graph:
save_path = './data/fitting_data'
if not os.path.exists(save_path):
os.makedirs(save_path)
# samp_dist = functools.partial(random.expovariate, 1)
samp_dist = 1
m_assy = 334
m_oft = 322
m_pnt = 263
Source = Source(env, "Source", data)
Sink = Sink(env, "Sink", rec_lead_time=True, rec_arrivals=True)
Assembly = Process(env, "Assembly", m_assy,
qlimit=10000) # 조립 공정 작업장 수 = 200
Outfitting = Process(env, "Outfitting", m_oft,
qlimit=10000) # 의장 공정 작업장 수 = 185
Painting = Process(env, "Painting", m_pnt,
qlimit=10000) # 도장 공정 작업장 수 = 155
Monitor1 = Monitor(env, Assembly, samp_dist)
Monitor2 = Monitor(env, Outfitting, samp_dist)
Monitor3 = Monitor(env, Painting, samp_dist)
Source.out = Assembly
Assembly.out = Outfitting
Outfitting.out = Painting
Painting.out = Sink
save_graph = True
if save_graph:
save_path = './data/actual_data'
if not os.path.exists(save_path):
os.makedirs(save_path)
# samp_dist = functools.partial(random.expovariate, 1) # need to be checked
samp_dist = 1
m_assy = 334
m_oft = 322
m_pnt = 263
Source = Source(env, "Source", data)
Sink = Sink(env, 'Sink', rec_lead_time=True, rec_arrivals=True)
Assembly = Process(env, "Assembly", m_assy, qlimit=10000)
Outfitting = Process(env, "Outfitting", m_oft, qlimit=10000)
Painting = Process(env, "Painting", m_pnt, qlimit=10000)
# Connection
Source.out = Assembly
Assembly.out = Outfitting
Outfitting.out = Painting
Painting.out = Sink
Monitor1 = Monitor(env, Assembly, samp_dist)
Monitor2 = Monitor(env, Outfitting, samp_dist)
Monitor3 = Monitor(env, Painting, samp_dist)
# Run it