[PAT甲级]1017. Queueing at Bank (25)(银行办理业务平均等待时间)

本文介绍了一个银行排队系统的模拟实现,通过记录每位顾客的到达时间和所需服务时间,计算出所有有效顾客的平均等待时间。该系统考虑了银行的实际营业时间限制,并确保了窗口服务的有效性和顾客的合理安排。

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1017. Queueing at Bank (25)

原题链接
相似题目 1014. Waiting in Line (30)
Suppose a bank has K windows open for service. There is a yellow line in front of the windows which devides the waiting area into two parts. All the customers have to wait in line behind the yellow line, until it is his/her turn to be served and there is a window available. It is assumed that no window can be occupied by a single customer for more than 1 hour.

Now given the arriving time T and the processing time P of each customer, you are supposed to tell the average waiting time of all the customers.

Input Specification:

Each input file contains one test case. For each case, the first line contains 2 numbers: N (<=10000) - the total number of customers, and K (<=100) - the number of windows. Then N lines follow, each contains 2 times: HH:MM:SS - the arriving time, and P - the processing time in minutes of a customer. Here HH is in the range [00, 23], MM and SS are both in [00, 59]. It is assumed that no two customers arrives at the same time.

Notice that the bank opens from 08:00 to 17:00. Anyone arrives early will have to wait in line till 08:00, and anyone comes too late (at or after 17:00:01) will not be served nor counted into the average.

Output Specification:

For each test case, print in one line the average waiting time of all the customers, in minutes and accurate up to 1 decimal place.

Sample Input:

7 3
07:55:00 16
17:00:01 2
07:59:59 15
08:01:00 60
08:00:00 30
08:00:02 2
08:03:00 10

Sample Output:

8.2

题目大意:

  • 银行排队办理业务,有N个人,K个窗口
  • 给出N个人的到达银行时间,个人办理业务所需要的时间,求平均等待时间
  • 银行窗口08:00开始办理业务,下午17:00之后到达的人不接受办理,不算有效的人
  • 每个窗口前只能有一个人办理业务,其他的人均在黄线外等待,有窗口最先空闲(前一个人办理业务结束),等待的顾客就可以按照到达时间的先后顺序去办理

思路:

  • 定义结构体记录顾客到达时间come,办理业务所需要时间time
  • 为了方便计算,时间全部换成来计算
  • 统计并筛选所有办理业务的人,剔除17:00以后到达的人,按照到达时间排序
  • 如果顾客到达时间come大于窗口空闲时间windowTime,就可以直接办理业务,无需等待,否则等待总时间res += (windowTime - come)
  • 最终 等待总时间res/60/ 办理业务有效人数 = 人均等待时间
  • 注意res按秒计算,先换成分钟,再求平均等待时间

代码:

#include <iostream>
#include <cstdio>
#include <vector>
#include <algorithm>
using namespace std;
struct node{
    int come;//到达时间
    int time;//办理业务所需要时间
};
int cmp(node a, node b){
    return a.come < b.come;
}
int main()
{
    int n, k;//n个人 k个窗口
    scanf("%d %d", &n, &k);
    vector<node> custom;
    for(int i=0; i<n; i++){
        int hh,mm,ss,time;
        scanf("%d:%d:%d %d", &hh, &mm, &ss, &time);
        int cometime = hh*3600 + mm*60 + ss;
        if(cometime > 61200)//顾客来的时间晚于17:00 无效 直接跳过,无法办理
            continue;
        node temp;
        temp.come = cometime;
        temp.time = time*60;
        custom.push_back(temp);
    }
    sort(custom.begin(), custom.end(), cmp);
    vector<int> windowTime(k, 28800);//28800代表早上八点
    double res = 0.0;
    for(int i=0; i<custom.size(); i++){
        int minWindow=0;//最早结束的窗口 最早结束的窗口时间
        for(int j=1; j<k; j++){
            if(windowTime[minWindow] > windowTime[j]){
                minWindow = j;
            }
        }
        if(windowTime[minWindow] <= custom[i].come){//顾客来的时候就有空闲窗口
            windowTime[minWindow] = custom[i].come + custom[i].time;
        }else{//顾客来的时候需要等待
            res += (windowTime[minWindow] - custom[i].come);//顾客等待时间
            windowTime[minWindow] +=  custom[i].time;//更新窗口空闲时间
        }
    }
    if(custom.size() == 0){//有效人数为0,直接输出,除以0无意义
        printf("0.0");
    }else{
        printf("%.1f", res/60.0/custom.size());
    }
    return 0;
}
### 银行排队问题的Python实现 银行排队问题是典型的并行处理和任务分配场景,可以通过ZeroMQ框架中的Ventilator-Worker-Sink模型来解决[^1]。以下是基于该模型的一个简单Python实现: #### ZeroMQ Ventilator 实现 Ventilator负责生成任务并将它们发送给Workers。 ```python import zmq import time context = zmq.Context() # Socket to send tasks to workers sender = context.socket(zmq.PUSH) sender.bind("tcp://*:5557") print("Press Enter when the workers are ready...") _ = input() print("Sending tasks to workers...") # Send out tasks total_msec = 0 for task_nbr in range(100): workload = int((task_nbr * task_nbr) % 100 + 1) # Some random work load total_msec += workload sender.send_string(str(workload)) print(f"Total expected cost: {total_msec} msec") time.sleep(1) # Give 0MQ time to deliver ``` #### ZeroMQ Worker 实现 Worker接收来自Ventilator的任务并执行计算后将结果返回给Sink。 ```python import zmq import sys import time context = zmq.Context() # Socket to receive messages on receiver = context.socket(zmq.PULL) receiver.connect("tcp://localhost:5557") # Socket to send messages to sender = context.socket(zmq.PUSH) sender.connect("tcp://localhost:5558") while True: s = receiver.recv_string() print(f"Received request: {s}") # Do some 'work' time.sleep(int(s) / 10) # Send results to sink sender.send(b'') ``` #### ZeroMQ Sink 实现 Sink收集所有Worker的结果,并统计完成时间。 ```python import zmq import time context = zmq.Context() # Socket to collect worker responses receiver = context.socket(zmq.PULL) receiver.bind("tcp://*:5558") # Wait for start of batch s = receiver.recv() # Start our clock now tstart = time.time() # Process 100 confirmations for task_nbr in range(100): s = receiver.recv() if task_nbr % 10 == 0: sys.stdout.write(':') else: sys.stdout.write('.') sys.stdout.flush() # Calculate and report duration of batch tend = time.time() print(f"\nTotal elapsed time: {(tend-tstart)*1000} msec") ``` 上述代码展示了如何通过ZeroMQ构建一个简单的分布式任务管理系统[^2]。对于银行排队问题,可以将其视为多个客户作为任务被分配到不同的柜员(即Worker),而最终的结果由Sink汇总。 此外,在高并发环境下,还需要注意内存管理和I/O性能优化[^3]。建议使用缓存机制减少磁盘操作频率,并利用消息队列实现各模块间的异步通信。
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