{"id":1168271,"date":"2025-01-15T15:55:58","date_gmt":"2025-01-15T07:55:58","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1168271.html"},"modified":"2025-01-15T15:56:01","modified_gmt":"2025-01-15T07:56:01","slug":"%e5%a6%82%e4%bd%95%e7%94%a8python%e5%ae%9e%e7%8e%b0%e6%8e%92%e9%98%9f%e8%ae%ba","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1168271.html","title":{"rendered":"\u5982\u4f55\u7528python\u5b9e\u73b0\u6392\u961f\u8bba"},"content":{"rendered":"

\"\u5982\u4f55\u7528python\u5b9e\u73b0\u6392\u961f\u8bba\"<\/p>\n

\u4f7f\u7528Python\u5b9e\u73b0\u6392\u961f\u8bba<\/strong>\u7684\u6838\u5fc3\u5728\u4e8e\u4f7f\u7528\u5408\u9002\u7684\u6570\u636e\u7ed3\u6784\u548c\u7b97\u6cd5\u6765\u6a21\u62df\u6392\u961f\u7cfb\u7edf\u3002\u6211\u4eec\u53ef\u4ee5\u5229\u7528Python\u7684\u5185\u7f6e\u5e93\u548c\u4e00\u4e9b\u7b2c\u4e09\u65b9\u5e93\u6765\u5b9e\u73b0\u6392\u961f\u8bba\u6a21\u578b\uff0c\u5982\u961f\u5217\u3001\u79bb\u6563\u4e8b\u4ef6\u4eff\u771f\u3001\u7edf\u8ba1\u5206\u6790<\/strong>\u3002\u4e0b\u9762\u6211\u5c06\u8be6\u7ec6\u63cf\u8ff0\u5982\u4f55\u7528Python\u5b9e\u73b0\u6392\u961f\u8bba\u3002<\/p>\n<\/p>\n

\u4e00\u3001\u6392\u961f\u8bba\u7b80\u4ecb<\/h3>\n<\/p>\n

\u6392\u961f\u8bba\u662f\u7814\u7a76\u6392\u961f\u7cfb\u7edf\u884c\u4e3a\u7684\u4e00\u95e8\u5b66\u95ee\uff0c\u4e3b\u8981\u5173\u6ce8\u5ba2\u6237\u5230\u8fbe\u3001\u670d\u52a1\u548c\u79bb\u5f00\u7684\u8fc7\u7a0b\u3002\u6392\u961f\u8bba\u6a21\u578b\u901a\u5e38\u7531\u4e09\u4e2a\u4e3b\u8981\u7ec4\u6210\u90e8\u5206\u6784\u6210\uff1a\u5230\u8fbe\u8fc7\u7a0b\u3001\u670d\u52a1\u673a\u5236\u3001\u6392\u961f\u89c4\u5219<\/strong>\u3002\u901a\u8fc7\u8fd9\u4e9b\u6a21\u578b\uff0c\u6211\u4eec\u53ef\u4ee5\u5206\u6790\u7cfb\u7edf\u6027\u80fd\u6307\u6807\uff0c\u5982\u7b49\u5f85\u65f6\u95f4\u3001\u7cfb\u7edf\u5229\u7528\u7387\u3001\u670d\u52a1\u6c34\u5e73<\/strong>\u7b49\u3002<\/p>\n<\/p>\n

\u4e8c\u3001Python\u4e2d\u7684\u6392\u961f\u6a21\u62df<\/h3>\n<\/p>\n

1\u3001\u4f7f\u7528\u961f\u5217\u6570\u636e\u7ed3\u6784<\/h4>\n<\/p>\n

Python\u63d0\u4f9b\u4e86queue<\/code>\u6a21\u5757\uff0c\u53ef\u4ee5\u7528\u4e8e\u5b9e\u73b0FIFO\uff08\u5148\u5165\u5148\u51fa\uff09\u961f\u5217\uff0c\u8fd9\u4e0e\u5927\u591a\u6570\u6392\u961f\u7cfb\u7edf\u7684\u884c\u4e3a\u4e00\u81f4\u3002\u961f\u5217\u662f\u6392\u961f\u8bba\u7684\u6838\u5fc3\u6570\u636e\u7ed3\u6784\uff0c\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528queue.Queue<\/code>\u6765\u521b\u5efa\u548c\u7ba1\u7406\u5ba2\u6237\u961f\u5217\u3002<\/p>\n<\/p>\n

import queue<\/p>\n
\u521b\u5efa\u4e00\u4e2a\u961f\u5217<\/strong><\/h2>\n
q = queue.Queue()<\/p>\n
\u6dfb\u52a0\u5ba2\u6237\u5230\u961f\u5217<\/strong><\/h2>\n
q.put('Customer 1')<\/p>\n
q.put('Customer 2')<\/p>\n
\u4ece\u961f\u5217\u4e2d\u53d6\u51fa\u5ba2\u6237<\/strong><\/h2>\n
customer = q.get()<\/p>\n
print(customer)  # \u8f93\u51fa: Customer 1<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u79bb\u6563\u4e8b\u4ef6\u4eff\u771f<\/h4>\n<\/p>\n
\u79bb\u6563\u4e8b\u4ef6\u4eff\u771f\u662f\u6a21\u62df\u6392\u961f\u7cfb\u7edf\u7684\u4e00\u79cd\u5e38\u89c1\u65b9\u6cd5\uff0c\u901a\u8fc7\u6a21\u62df\u4e8b\u4ef6\uff08\u5982\u5ba2\u6237\u5230\u8fbe\u3001\u670d\u52a1\u5f00\u59cb\u3001\u670d\u52a1\u7ed3\u675f\uff09\u6765\u5206\u6790\u7cfb\u7edf\u884c\u4e3a\u3002Python\u7684simpy<\/code>\u5e93\u662f\u4e00\u4e2a\u5f3a\u5927\u7684\u79bb\u6563\u4e8b\u4ef6\u4eff\u771f\u5de5\u5177\u3002<\/p>\n<\/p>\n
import simpy<\/p>\n
def customer(env, name, server):<\/p>\n
    arrival_time = env.now<\/p>\n
    print(f'{name} \u5230\u8fbe\u65f6\u95f4 {arrival_time}')<\/p>\n
    with server.request() as request:<\/p>\n
        yield request<\/p>\n
        wAI<\/a>t = env.now - arrival_time<\/p>\n
        print(f'{name} \u7b49\u5f85\u65f6\u95f4 {wait}')<\/p>\n
        service_time = 5<\/p>\n
        yield env.timeout(service_time)<\/p>\n
        print(f'{name} \u79bb\u5f00\u65f6\u95f4 {env.now}')<\/p>\n
\u521b\u5efa\u73af\u5883\u548c\u670d\u52a1\u5668<\/strong><\/h2>\n
env = simpy.Environment()<\/p>\n
server = simpy.Resource(env, capacity=1)<\/p>\n
\u751f\u6210\u5ba2\u6237<\/strong><\/h2>\n
env.process(customer(env, 'Customer 1', server))<\/p>\n
env.process(customer(env, 'Customer 2', server))<\/p>\n
\u8fd0\u884c\u4eff\u771f<\/strong><\/h2>\n
env.run()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e09\u3001\u6392\u961f\u8bba\u6a21\u578b\u548c\u5206\u6790<\/h3>\n<\/p>\n
1\u3001M\/M\/1 \u6392\u961f\u6a21\u578b<\/h4>\n<\/p>\n
M\/M\/1\u6a21\u578b\u662f\u6700\u7b80\u5355\u7684\u6392\u961f\u8bba\u6a21\u578b\uff0c\u8868\u793a\u5355\u670d\u52a1\u5668\u3001\u6cca\u677e\u5230\u8fbe\u3001\u6307\u6570\u670d\u52a1\u65f6\u95f4\u3002\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528Python\u6765\u6a21\u62df\u548c\u5206\u6790M\/M\/1\u7cfb\u7edf\u3002<\/p>\n<\/p>\n
import numpy as np<\/p>\n
import simpy<\/p>\n
def mm1_queue(env, arrival_rate, service_rate):<\/p>\n
    server = simpy.Resource(env, capacity=1)<\/p>\n
    while True:<\/p>\n
        inter_arrival = np.random.exponential(1\/arrival_rate)<\/p>\n
        yield env.timeout(inter_arrival)<\/p>\n
        env.process(customer(env, server, service_rate))<\/p>\n
def customer(env, server, service_rate):<\/p>\n
    arrival_time = env.now<\/p>\n
    with server.request() as request:<\/p>\n
        yield request<\/p>\n
        wait = env.now - arrival_time<\/p>\n
        service_time = np.random.exponential(1\/service_rate)<\/p>\n
        yield env.timeout(service_time)<\/p>\n
\u53c2\u6570\u8bbe\u7f6e<\/strong><\/h2>\n
arrival_rate = 2  # \u5230\u8fbe\u7387 \u03bb<\/p>\n
service_rate = 3  # \u670d\u52a1\u7387 \u03bc<\/p>\n
\u521b\u5efa\u73af\u5883\u548c\u8fd0\u884c\u4eff\u771f<\/strong><\/h2>\n
env = simpy.Environment()<\/p>\n
env.process(mm1_queue(env, arrival_rate, service_rate))<\/p>\n
env.run(until=100)<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u6027\u80fd\u6307\u6807\u5206\u6790<\/h4>\n<\/p>\n
\u901a\u8fc7\u4eff\u771f\uff0c\u6211\u4eec\u53ef\u4ee5\u8ba1\u7b97\u548c\u5206\u6790\u6392\u961f\u7cfb\u7edf\u7684\u6027\u80fd\u6307\u6807\uff0c\u5982\u5e73\u5747\u7b49\u5f85\u65f6\u95f4\u3001\u7cfb\u7edf\u5229\u7528\u7387\u3001\u5e73\u5747\u6392\u961f\u957f\u5ea6<\/strong>\u7b49\u3002<\/p>\n<\/p>\n
import numpy as np<\/p>\n
import simpy<\/p>\n
\u5b9a\u4e49\u5168\u5c40\u53d8\u91cf\u6765\u5b58\u50a8\u7edf\u8ba1\u6570\u636e<\/strong><\/h2>\n
wait_times = []<\/p>\n
def mm1_queue(env, arrival_rate, service_rate):<\/p>\n
    server = simpy.Resource(env, capacity=1)<\/p>\n
    while True:<\/p>\n
        inter_arrival = np.random.exponential(1\/arrival_rate)<\/p>\n
        yield env.timeout(inter_arrival)<\/p>\n
        env.process(customer(env, server, service_rate))<\/p>\n
def customer(env, server, service_rate):<\/p>\n
    arrival_time = env.now<\/p>\n
    with server.request() as request:<\/p>\n
        yield request<\/p>\n
        wait = env.now - arrival_time<\/p>\n
        wait_times.append(wait)<\/p>\n
        service_time = np.random.exponential(1\/service_rate)<\/p>\n
        yield env.timeout(service_time)<\/p>\n
\u53c2\u6570\u8bbe\u7f6e<\/strong><\/h2>\n
arrival_rate = 2  # \u5230\u8fbe\u7387 \u03bb<\/p>\n
service_rate = 3  # \u670d\u52a1\u7387 \u03bc<\/p>\n
\u521b\u5efa\u73af\u5883\u548c\u8fd0\u884c\u4eff\u771f<\/strong><\/h2>\n
env = simpy.Environment()<\/p>\n
env.process(mm1_queue(env, arrival_rate, service_rate))<\/p>\n
env.run(until=1000)<\/p>\n
\u8ba1\u7b97\u548c\u8f93\u51fa\u6027\u80fd\u6307\u6807<\/strong><\/h2>\n
average_wait = np.mean(wait_times)<\/p>\n
utilization = arrival_rate \/ service_rate<\/p>\n
print(f'\u5e73\u5747\u7b49\u5f85\u65f6\u95f4: {average_wait}')<\/p>\n
print(f'\u7cfb\u7edf\u5229\u7528\u7387: {utilization}')<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u56db\u3001\u6269\u5c55\u6a21\u578b<\/h3>\n<\/p>\n
1\u3001M\/M\/c \u6392\u961f\u6a21\u578b<\/h4>\n<\/p>\n
M\/M\/c\u6a21\u578b\u662f\u591a\u670d\u52a1\u5668\u6392\u961f\u7cfb\u7edf\uff0c\u8868\u793ac\u4e2a\u5e76\u884c\u670d\u52a1\u5668\u3001\u6cca\u677e\u5230\u8fbe\u3001\u6307\u6570\u670d\u52a1\u65f6\u95f4\u3002\u6211\u4eec\u53ef\u4ee5\u6269\u5c55\u4e4b\u524d\u7684\u4ee3\u7801\u6765\u6a21\u62dfM\/M\/c\u7cfb\u7edf\u3002<\/p>\n<\/p>\n
import numpy as np<\/p>\n
import simpy<\/p>\n
\u5b9a\u4e49\u5168\u5c40\u53d8\u91cf\u6765\u5b58\u50a8\u7edf\u8ba1\u6570\u636e<\/strong><\/h2>\n
wait_times = []<\/p>\n
def mmc_queue(env, arrival_rate, service_rate, num_servers):<\/p>\n
    server = simpy.Resource(env, capacity=num_servers)<\/p>\n
    while True:<\/p>\n
        inter_arrival = np.random.exponential(1\/arrival_rate)<\/p>\n
        yield env.timeout(inter_arrival)<\/p>\n
        env.process(customer(env, server, service_rate))<\/p>\n
def customer(env, server, service_rate):<\/p>\n
    arrival_time = env.now<\/p>\n
    with server.request() as request:<\/p>\n
        yield request<\/p>\n
        wait = env.now - arrival_time<\/p>\n
        wait_times.append(wait)<\/p>\n
        service_time = np.random.exponential(1\/service_rate)<\/p>\n
        yield env.timeout(service_time)<\/p>\n
\u53c2\u6570\u8bbe\u7f6e<\/strong><\/h2>\n
arrival_rate = 2  # \u5230\u8fbe\u7387 \u03bb<\/p>\n
service_rate = 3  # \u670d\u52a1\u7387 \u03bc<\/p>\n
num_servers = 2  # \u670d\u52a1\u5668\u6570\u91cf c<\/p>\n
\u521b\u5efa\u73af\u5883\u548c\u8fd0\u884c\u4eff\u771f<\/strong><\/h2>\n
env = simpy.Environment()<\/p>\n
env.process(mmc_queue(env, arrival_rate, service_rate, num_servers))<\/p>\n
env.run(until=1000)<\/p>\n
\u8ba1\u7b97\u548c\u8f93\u51fa\u6027\u80fd\u6307\u6807<\/strong><\/h2>\n
average_wait = np.mean(wait_times)<\/p>\n
utilization = arrival_rate \/ (service_rate * num_servers)<\/p>\n
print(f'\u5e73\u5747\u7b49\u5f85\u65f6\u95f4: {average_wait}')<\/p>\n
print(f'\u7cfb\u7edf\u5229\u7528\u7387: {utilization}')<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001M\/D\/1 \u6392\u961f\u6a21\u578b<\/h4>\n<\/p>\n
M\/D\/1\u6a21\u578b\u8868\u793a\u5355\u670d\u52a1\u5668\u3001\u6cca\u677e\u5230\u8fbe\u3001\u786e\u5b9a\u670d\u52a1\u65f6\u95f4\u3002\u6211\u4eec\u53ef\u4ee5\u901a\u8fc7\u4fee\u6539\u670d\u52a1\u65f6\u95f4\u5206\u5e03\u6765\u5b9e\u73b0M\/D\/1\u7cfb\u7edf\u3002<\/p>\n<\/p>\n
import numpy as np<\/p>\n
import simpy<\/p>\n
\u5b9a\u4e49\u5168\u5c40\u53d8\u91cf\u6765\u5b58\u50a8\u7edf\u8ba1\u6570\u636e<\/strong><\/h2>\n
wait_times = []<\/p>\n
def md1_queue(env, arrival_rate, service_time):<\/p>\n
    server = simpy.Resource(env, capacity=1)<\/p>\n
    while True:<\/p>\n
        inter_arrival = np.random.exponential(1\/arrival_rate)<\/p>\n
        yield env.timeout(inter_arrival)<\/p>\n
        env.process(customer(env, server, service_time))<\/p>\n
def customer(env, server, service_time):<\/p>\n
    arrival_time = env.now<\/p>\n
    with server.request() as request:<\/p>\n
        yield request<\/p>\n
        wait = env.now - arrival_time<\/p>\n
        wait_times.append(wait)<\/p>\n
        yield env.timeout(service_time)<\/p>\n
\u53c2\u6570\u8bbe\u7f6e<\/strong><\/h2>\n
arrival_rate = 2  # \u5230\u8fbe\u7387 \u03bb<\/p>\n
service_time = 1\/3  # \u786e\u5b9a\u670d\u52a1\u65f6\u95f4<\/p>\n
\u521b\u5efa\u73af\u5883\u548c\u8fd0\u884c\u4eff\u771f<\/strong><\/h2>\n
env = simpy.Environment()<\/p>\n
env.process(md1_queue(env, arrival_rate, service_time))<\/p>\n
env.run(until=1000)<\/p>\n
\u8ba1\u7b97\u548c\u8f93\u51fa\u6027\u80fd\u6307\u6807<\/strong><\/h2>\n
average_wait = np.mean(wait_times)<\/p>\n
utilization = arrival_rate * service_time<\/p>\n
print(f'\u5e73\u5747\u7b49\u5f85\u65f6\u95f4: {average_wait}')<\/p>\n
print(f'\u7cfb\u7edf\u5229\u7528\u7387: {utilization}')<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e94\u3001\u590d\u6742\u6392\u961f\u7cfb\u7edf<\/h3>\n<\/p>\n
1\u3001\u4f18\u5148\u7ea7\u6392\u961f<\/h4>\n<\/p>\n
\u5728\u67d0\u4e9b\u7cfb\u7edf\u4e2d\uff0c\u4e0d\u540c\u7c7b\u578b\u7684\u5ba2\u6237\u53ef\u80fd\u6709\u4e0d\u540c\u7684\u4f18\u5148\u7ea7\u3002\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528simpy.PriorityResource<\/code>\u6765\u5b9e\u73b0\u4f18\u5148\u7ea7\u6392\u961f\u3002<\/p>\n<\/p>\n
import numpy as np<\/p>\n
import simpy<\/p>\n
\u5b9a\u4e49\u5168\u5c40\u53d8\u91cf\u6765\u5b58\u50a8\u7edf\u8ba1\u6570\u636e<\/strong><\/h2>\n
wait_times = []<\/p>\n
def priority_queue(env, arrival_rate, service_rate):<\/p>\n
    server = simpy.PriorityResource(env, capacity=1)<\/p>\n
    while True:<\/p>\n
        inter_arrival = np.random.exponential(1\/arrival_rate)<\/p>\n
        yield env.timeout(inter_arrival)<\/p>\n
        priority = np.random.choice([0, 1])  # 0\u8868\u793a\u9ad8\u4f18\u5148\u7ea7\uff0c1\u8868\u793a\u4f4e\u4f18\u5148\u7ea7<\/p>\n
        env.process(customer(env, server, service_rate, priority))<\/p>\n
def customer(env, server, service_rate, priority):<\/p>\n
    arrival_time = env.now<\/p>\n
    with server.request(priority=priority) as request:<\/p>\n
        yield request<\/p>\n
        wait = env.now - arrival_time<\/p>\n
        wait_times.append(wait)<\/p>\n
        service_time = np.random.exponential(1\/service_rate)<\/p>\n
        yield env.timeout(service_time)<\/p>\n
\u53c2\u6570\u8bbe\u7f6e<\/strong><\/h2>\n
arrival_rate = 2  # \u5230\u8fbe\u7387 \u03bb<\/p>\n
service_rate = 3  # \u670d\u52a1\u7387 \u03bc<\/p>\n
\u521b\u5efa\u73af\u5883\u548c\u8fd0\u884c\u4eff\u771f<\/strong><\/h2>\n
env = simpy.Environment()<\/p>\n
env.process(priority_queue(env, arrival_rate, service_rate))<\/p>\n
env.run(until=1000)<\/p>\n
\u8ba1\u7b97\u548c\u8f93\u51fa\u6027\u80fd\u6307\u6807<\/strong><\/h2>\n
average_wait = np.mean(wait_times)<\/p>\n
utilization = arrival_rate \/ service_rate<\/p>\n
print(f'\u5e73\u5747\u7b49\u5f85\u65f6\u95f4: {average_wait}')<\/p>\n
print(f'\u7cfb\u7edf\u5229\u7528\u7387: {utilization}')<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u7f51\u7edc\u6392\u961f\u7cfb\u7edf<\/h4>\n<\/p>\n
\u5728\u66f4\u590d\u6742\u7684\u7cfb\u7edf\u4e2d\uff0c\u5ba2\u6237\u53ef\u80fd\u9700\u8981\u901a\u8fc7\u591a\u4e2a\u670d\u52a1\u5668\u3002\u8fd9\u79cd\u60c5\u51b5\u53ef\u4ee5\u901a\u8fc7\u591a\u4e2a\u6392\u961f\u7cfb\u7edf\u7684\u7ec4\u5408\u6765\u6a21\u62df\u3002<\/p>\n<\/p>\n
import numpy as np<\/p>\n
import simpy<\/p>\n
\u5b9a\u4e49\u5168\u5c40\u53d8\u91cf\u6765\u5b58\u50a8\u7edf\u8ba1\u6570\u636e<\/strong><\/h2>\n
wait_times = []<\/p>\n
def network_queue(env, arrival_rate, service_rate):<\/p>\n
    server1 = simpy.Resource(env, capacity=1)<\/p>\n
    server2 = simpy.Resource(env, capacity=1)<\/p>\n
    while True:<\/p>\n
        inter_arrival = np.random.exponential(1\/arrival_rate)<\/p>\n
        yield env.timeout(inter_arrival)<\/p>\n
        env.process(customer(env, server1, server2, service_rate))<\/p>\n
def customer(env, server1, server2, service_rate):<\/p>\n
    arrival_time = env.now<\/p>\n
    with server1.request() as request1:<\/p>\n
        yield request1<\/p>\n
        wait1 = env.now - arrival_time<\/p>\n
        wait_times.append(wait1)<\/p>\n
        service_time1 = np.random.exponential(1\/service_rate)<\/p>\n
        yield env.timeout(service_time1)<\/p>\n
    with server2.request() as request2:<\/p>\n
        yield request2<\/p>\n
        wait2 = env.now - arrival_time<\/p>\n
        wait_times.append(wait2)<\/p>\n
        service_time2 = np.random.exponential(1\/service_rate)<\/p>\n
        yield env.timeout(service_time2)<\/p>\n
\u53c2\u6570\u8bbe\u7f6e<\/strong><\/h2>\n
arrival_rate = 2  # \u5230\u8fbe\u7387 \u03bb<\/p>\n
service_rate = 3  # \u670d\u52a1\u7387 \u03bc<\/p>\n
\u521b\u5efa\u73af\u5883\u548c\u8fd0\u884c\u4eff\u771f<\/strong><\/h2>\n
env = simpy.Environment()<\/p>\n
env.process(network_queue(env, arrival_rate, service_rate))<\/p>\n
env.run(until=1000)<\/p>\n
\u8ba1\u7b97\u548c\u8f93\u51fa\u6027\u80fd\u6307\u6807<\/strong><\/h2>\n
average_wait = np.mean(wait_times)<\/p>\n
utilization = arrival_rate \/ service_rate<\/p>\n
print(f'\u5e73\u5747\u7b49\u5f85\u65f6\u95f4: {average_wait}')<\/p>\n
print(f'\u7cfb\u7edf\u5229\u7528\u7387: {utilization}')<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u516d\u3001\u6392\u961f\u8bba\u5e94\u7528\u5b9e\u4f8b<\/h3>\n<\/p>\n
1\u3001\u94f6\u884c\u670d\u52a1\u7cfb\u7edf<\/h4>\n<\/p>\n
\u5728\u94f6\u884c\u670d\u52a1\u7cfb\u7edf\u4e2d\uff0c\u5ba2\u6237\u5230\u8fbe\u94f6\u884c\u6392\u961f\u7b49\u5f85\u670d\u52a1\u3002\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528\u6392\u961f\u8bba\u6a21\u578b\u6765\u5206\u6790\u5ba2\u6237\u7b49\u5f85\u65f6\u95f4\u548c\u7cfb\u7edf\u5229\u7528\u7387\u3002<\/p>\n<\/p>\n
import numpy as np<\/p>\n
import simpy<\/p>\n
\u5b9a\u4e49\u5168\u5c40\u53d8\u91cf\u6765\u5b58\u50a8\u7edf\u8ba1\u6570\u636e<\/strong><\/h2>\n
wait_times = []<\/p>\n
def bank_queue(env, arrival_rate, service_rate, num_tellers):<\/p>\n
    tellers = simpy.Resource(env, capacity=num_tellers)<\/p>\n
    while True:<\/p>\n
        inter_arrival = np.random.exponential(1\/arrival_rate)<\/p>\n
        yield env.timeout(inter_arrival)<\/p>\n
        env.process(customer(env, tellers, service_rate))<\/p>\n
def customer(env, tellers, service_rate):<\/p>\n
    arrival_time = env.now<\/p>\n
    with tellers.request() as request:<\/p>\n
        yield request<\/p>\n
        wait = env.now - arrival_time<\/p>\n
        wait_times.append(wait)<\/p>\n
        service_time = np.random.exponential(1\/service_rate)<\/p>\n
        yield env.timeout(service_time)<\/p>\n
\u53c2\u6570\u8bbe\u7f6e<\/strong><\/h2>\n
arrival_rate = 2  # \u5230\u8fbe\u7387 \u03bb<\/p>\n
service_rate = 3  # \u670d\u52a1\u7387 \u03bc<\/p>\n
num_tellers = 2  # \u51fa\u7eb3\u5458\u6570\u91cf<\/p>\n
\u521b\u5efa\u73af\u5883\u548c\u8fd0\u884c\u4eff\u771f<\/strong><\/h2>\n
env = simpy.Environment()<\/p>\n
env.process(bank_queue(env, arrival_rate, service_rate, num_tellers))<\/p>\n
env.run(until=1000)<\/p>\n
\u8ba1\u7b97\u548c\u8f93\u51fa\u6027\u80fd\u6307\u6807<\/strong><\/h2>\n
average_wait = np.mean(wait_times)<\/p>\n
utilization = arrival_rate \/ (service_rate * num_tellers)<\/p>\n
print(f'\u5e73\u5747\u7b49\u5f85\u65f6\u95f4: {average_wait}')<\/p>\n
print(f'\u7cfb\u7edf\u5229\u7528\u7387: {utilization}')<\/p>\n
<\/code><\/pre>\n<\/p>\n
2\u3001\u547c\u53eb\u4e2d\u5fc3<\/h4>\n<\/p>\n
\u5728\u547c\u53eb\u4e2d\u5fc3\u4e2d\uff0c\u5ba2\u6237\u901a\u8fc7\u7535\u8bdd\u6392\u961f\u7b49\u5f85\u5ba2\u670d\u4ee3\u8868\u7684\u670d\u52a1\u3002\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528\u6392\u961f\u8bba\u6a21\u578b\u6765\u5206\u6790\u5ba2\u6237\u7b49\u5f85\u65f6\u95f4\u548c\u7cfb\u7edf\u5229\u7528\u7387\u3002<\/p>\n<\/p>\n
import numpy as np<\/p>\n
import simpy<\/p>\n
\u5b9a\u4e49\u5168\u5c40\u53d8\u91cf\u6765\u5b58\u50a8\u7edf\u8ba1\u6570\u636e<\/strong><\/h2>\n
wait_times = []<\/p>\n
def call_center_queue(env, arrival_rate, service_rate, num_agents):<\/p>\n
    agents = simpy.Resource(env, capacity=num_agents)<\/p>\n
    while True:<\/p>\n
        inter_arrival = np.random.exponential(1\/arrival_rate)<\/p>\n
        yield env.timeout(inter_arrival)<\/p>\n
        env.process(customer(env, agents, service_rate))<\/p>\n
def customer(env, agents, service_rate):<\/p>\n
    arrival_time = env.now<\/p>\n
    with agents.request() as request:<\/p>\n
        yield request<\/p>\n
        wait = env.now - arrival_time<\/p>\n
        wait_times.append(wait)<\/p>\n
        service_time = np.random.exponential(1\/service_rate)<\/p>\n
        yield env.timeout(service_time)<\/p>\n
\u53c2\u6570\u8bbe\u7f6e<\/strong><\/h2>\n
arrival_rate = 2  # \u5230\u8fbe\u7387 \u03bb<\/p>\n
service_rate = 3  # \u670d\u52a1\u7387 \u03bc<\/p>\n
num_agents = 3  # \u5ba2\u670d\u4ee3\u8868\u6570\u91cf<\/p>\n
\u521b\u5efa\u73af\u5883\u548c\u8fd0\u884c\u4eff\u771f<\/strong><\/h2>\n
env = simpy.Environment()<\/p>\n
env.process(call_center_queue(env, arrival_rate, service_rate, num_agents))<\/p>\n
env.run(until=1000)<\/p>\n
\u8ba1\u7b97\u548c\u8f93\u51fa\u6027\u80fd\u6307\u6807<\/strong><\/h2>\n
average_wait = np.mean(wait_times)<\/p>\n
utilization = arrival_rate \/ (service_rate * num_agents)<\/p>\n
print(f'\u5e73\u5747\u7b49\u5f85\u65f6\u95f4: {average_wait}')<\/p>\n
print(f'\u7cfb\u7edf\u5229\u7528\u7387: {utilization}')<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e03\u3001\u603b\u7ed3<\/h3>\n<\/p>\n
\u901a\u8fc7\u4e0a\u8ff0\u5185\u5bb9\uff0c\u6211\u4eec\u8be6\u7ec6\u4ecb\u7ecd\u4e86\u5982\u4f55\u7528Python\u5b9e\u73b0\u6392\u961f\u8bba<\/strong>\uff0c\u5305\u62ec\u57fa\u672c\u6982\u5ff5\u3001\u961f\u5217\u6570\u636e\u7ed3\u6784\u3001\u79bb\u6563\u4e8b\u4ef6\u4eff\u771f\u3001M\/M\/1\u6a21\u578b\u3001\u6269\u5c55\u6a21\u578b\u3001\u6027\u80fd\u6307\u6807\u5206\u6790\u3001\u590d\u6742\u6392\u961f\u7cfb\u7edf\u548c\u5b9e\u9645\u5e94\u7528\u5b9e\u4f8b\u3002\u4f7f\u7528Python\u548csimpy<\/code>\u5e93\uff0c\u6211\u4eec\u80fd\u591f\u6709\u6548\u5730\u6a21\u62df\u548c\u5206\u6790\u5404\u79cd\u6392\u961f\u7cfb\u7edf\uff0c\u5e2e\u52a9\u6211\u4eec\u4f18\u5316\u7cfb\u7edf\u6027\u80fd\u3001\u63d0\u9ad8\u670d\u52a1\u6c34\u5e73\u3002\u901a\u8fc7\u4e0d\u65ad\u7684\u4eff\u771f\u548c\u5206\u6790\uff0c\u6211\u4eec\u53ef\u4ee5\u83b7\u5f97\u5bf9\u6392\u961f\u7cfb\u7edf\u66f4\u6df1\u523b\u7684\u7406\u89e3\uff0c\u5e76\u4e3a\u5b9e\u9645\u5e94\u7528\u63d0\u4f9b\u6709\u4ef7\u503c\u7684\u6307\u5bfc\u3002<\/p>\n<\/p>\n
\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
 \u4ec0\u4e48\u662f\u6392\u961f\u8bba\uff0c\u5b83\u5728\u5b9e\u9645\u5e94\u7528\u4e2d\u6709\u54ea\u4e9b\u573a\u666f\uff1f<\/strong>
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\u4f7f\u7528Python\u5b9e\u73b0\u6392\u961f\u8bba\u6a21\u578b\u9700\u8981\u54ea\u4e9b\u57fa\u672c\u77e5\u8bc6\uff1f<\/strong>
\u8981\u4f7f\u7528Python\u5b9e\u73b0\u6392\u961f\u8bba\u6a21\u578b\uff0c\u9996\u5148\u9700\u8981\u638c\u63e1\u57fa\u7840\u7684\u6982\u7387\u8bba\u548c\u7edf\u8ba1\u5b66\u77e5\u8bc6\uff0c\u56e0\u4e3a\u6392\u961f\u8bba\u7684\u6838\u5fc3\u5728\u4e8e\u5bf9\u968f\u673a\u8fc7\u7a0b\u7684\u5206\u6790\u3002\u6b64\u5916\uff0c\u719f\u7ec3\u4f7f\u7528Python\u53ca\u5176\u76f8\u5173\u5e93\uff08\u5982NumPy\u3001SciPy\u548cMatplotlib\uff09\u4e5f\u662f\u5fc5\u8981\u7684\u3002\u8fd9\u4e9b\u5de5\u5177\u53ef\u4ee5\u5e2e\u52a9\u4f60\u8fdb\u884c\u6570\u636e\u5206\u6790\u3001\u6a21\u578b\u6784\u5efa\u548c\u53ef\u89c6\u5316\uff0c\u589e\u5f3a\u5bf9\u6392\u961f\u7cfb\u7edf\u7684\u7406\u89e3\u3002<\/p>\n
\u5982\u4f55\u8bc4\u4f30\u6392\u961f\u7cfb\u7edf\u7684\u6027\u80fd\u6307\u6807\uff1f<\/strong>
\u8bc4\u4f30\u6392\u961f\u7cfb\u7edf\u7684\u6027\u80fd\u6307\u6807\u901a\u5e38\u5305\u62ec\u5e73\u5747\u7b49\u5f85\u65f6\u95f4\u3001\u7cfb\u7edf\u4e2d\u7684\u5e73\u5747\u987e\u5ba2\u6570\u91cf\u3001\u670d\u52a1\u5229\u7528\u7387\u7b49\u3002\u4f7f\u7528Python\u53ef\u4ee5\u901a\u8fc7\u6a21\u62df\u6216\u89e3\u6790\u65b9\u6cd5\u6765\u8ba1\u7b97\u8fd9\u4e9b\u6307\u6807\u3002\u4f8b\u5982\uff0c\u53ef\u4ee5\u901a\u8fc7Monte Carlo\u6a21\u62df\u6765\u4f30\u8ba1\u987e\u5ba2\u7684\u5e73\u5747\u7b49\u5f85\u65f6\u95f4\uff0c\u6216\u8005\u4f7f\u7528\u6392\u961f\u6a21\u578b\u516c\u5f0f\uff08\u5982M\/M\/1\u6a21\u578b\uff09\u76f4\u63a5\u8ba1\u7b97\u6027\u80fd\u6307\u6807\u3002\u8fd9\u4e9b\u6307\u6807\u80fd\u591f\u5e2e\u52a9\u51b3\u7b56\u8005\u4f18\u5316\u6392\u961f\u7cfb\u7edf\uff0c\u63d0\u9ad8\u670d\u52a1\u6548\u7387\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"\u4f7f\u7528Python\u5b9e\u73b0\u6392\u961f\u8bba\u7684\u6838\u5fc3\u5728\u4e8e\u4f7f\u7528\u5408\u9002\u7684\u6570\u636e\u7ed3\u6784\u548c\u7b97\u6cd5\u6765\u6a21\u62df\u6392\u961f\u7cfb\u7edf\u3002\u6211\u4eec\u53ef\u4ee5\u5229\u7528Python\u7684\u5185\u7f6e\u5e93\u548c […]","protected":false},"author":3,"featured_media":1168277,"comment_status":"closed","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[37],"tags":[],"acf":[],"_links":{"self":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1168271"}],"collection":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/comments?post=1168271"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1168271\/revisions"}],"predecessor-version":[{"id":1168279,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1168271\/revisions\/1168279"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1168277"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1168271"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1168271"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1168271"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}