[PAT甲级] 1017 Queueing at Bank (25)

本文介绍了一个银行排队系统的模拟算法,该算法通过计算每个顾客的平均等待时间来评估服务质量。考虑到银行的服务时间限制,即早上8点开门,下午5点停止接受新顾客,模拟程序能够准确计算出所有有效顾客的平均等待时间。

题目:

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


题目简介:计算一天中所有人在银行排队时长的平均值,8:00:00之前到达的顾客需要等待至8点银行开门,17:00:00之后到达的顾客由于银行关门,需要从计算的样本中去除(17点及之前到达可顺利办理业务)。

#include <iostream>
#include <stdlib.h>
#include <stdio.h>
#include <algorithm>
#include <queue>
using namespace std;

struct customer{
    int arrive;//顾客到达时间,以秒计
    int usetime;//办理业务时间,以秒计
}C[10000];

int gettime(int h, int m , int s){
    return h*3600 + m*60 + s;
}

bool cmp(customer c1, customer c2){
    return c1.arrive < c2.arrive;
}

int total(int N, int K){
    int i, k, totaltime = 0, window[100] = {0};
    //window记录了每一个窗口当前业务结束的时间
    queue<customer> q;

    //先处理8点之前到达的顾客
    for(i = k = 0; C[i].arrive < gettime(8, 0, 0); i++){
        q.push(C[i]);
        totaltime += gettime(8, 0, 0) - C[i].arrive;
    }
    while(!q.empty()){
        customer tmp = q.front();
        q.pop();
        if(k < K){
        window[k] += gettime(8, 0, 0) + tmp.usetime;
        k++;
        }
        //如果k==K,即所有窗口都满了,则需要等待,选一个值最小的window计算等待时间totaltime
        else if(k == K){
            sort(window, window+k);
            totaltime += (window[0] - gettime(8, 0, 0));
            window[0] += tmp.usetime;
        }
    }
    //当8点前的顾客都已经处理完后,处理剩下的顾客
    for(; i < N; i++){
        if(k < K){
            window[k] = C[i].arrive + C[i].usetime;
            k++;
        }
        //这里除了判断k==K,还要注意arrive>=window也是不需要等待的
        else if(k == K){
            sort(window, window+k);
            if(C[i].arrive < window[0]){
                totaltime += (window[0] - C[i].arrive);
                window[0] += C[i].usetime;
            }
            else
                window[0] = C[i].arrive + C[i].usetime;
        }
    }

    return totaltime;
}

int main(){
    int N, K, i, h, m, s, usetime, totaltime = 0;
    scanf("%d%d", &N, &K);
    for(i = 0; i < N; i++){
        scanf("%d:%d:%d %d", &h, &m, &s, &usetime);
        if(gettime(h, m, s) >= gettime(17, 0, 1)){
            i--;
            N--;
            continue;
        }
        C[i].arrive = gettime(h, m, s);
        C[i].usetime = usetime*60;//imput业务时间是以分钟计的
    }
    sort(C, C+i, cmp);//顾客按arrive顺序排序
    totaltime += total(i, K);
    printf("%.1f", totaltime/60.0/i);

    return 0;
}
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### 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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