问题描述:对 30000 个随机整数，利用插入排序、希尔排序、起泡排序、快速排序、选择排序、堆排序、归并排序等排序方法进行排序，并统计每一种排序上机所花费的时间。*输入的数据形式为任何一个正整数，大小不限。*输出的形式:数字大小逐个递增的数列C++实现

以下是一个简单的C++程序，它可以对输入的30000个随机整数进行排序，并统计每个排序算法的运行时间。其中包括插入排序、希尔排序、冒泡排序、快速排序、选择排序、堆排序和归并排序。

#include <iostream>
#include <cstdlib>
#include <ctime>
#include <chrono>
using namespace std;
using namespace std::chrono;

void insertionSort(int arr[], int n) {
    int i, key, j;
    for (i = 1; i < n; i++) {
        key = arr[i];
        j = i - 1;
        while (j >= 0 && arr[j] > key) {
            arr[j + 1] = arr[j];
            j = j - 1;
        }
        arr[j + 1] = key;
    }
}

void shellSort(int arr[], int n) {
    for (int gap = n/2; gap > 0; gap /= 2) {
        for (int i = gap; i < n; i += 1) {
            int temp = arr[i];
            int j;
            for (j = i; j >= gap && arr[j - gap] > temp; j -= gap) {
                arr[j] = arr[j - gap];
            }
            arr[j] = temp;
        }
    }
}

void bubbleSort(int arr[], int n) {
    for (int i = 0; i < n-1; i++) {
        for (int j = 0; j < n-i-1; j++) {
            if (arr[j] > arr[j+1]) {
                int temp = arr[j];
                arr[j] = arr[j+1];
                arr[j+1] = temp;
            }
        }
    }
}

int partition(int arr[], int low, int high) {
    int pivot = arr[high];
    int i = (low - 1);
    for (int j = low; j <= high- 1; j++) {
        if (arr[j] < pivot) {
            i++;
            int temp = arr[i];
            arr[i] = arr[j];
            arr[j] = temp;
        }
    }
    int temp = arr[i + 1];
    arr[i + 1] = arr[high];
    arr[high] = temp;
    return (i + 1);
}

void quickSort(int arr[], int low, int high) {
    if (low < high) {
        int pi = partition(arr, low, high);
        quickSort(arr, low, pi - 1);
        quickSort(arr, pi + 1, high);
    }
}

void selectionSort(int arr[], int n) {
    for (int i = 0; i < n-1; i++) {
        int min_idx = i;
        for (int j = i+1; j < n; j++) {
            if (arr[j] < arr[min_idx]) {
                min_idx = j;
            }
        }
        int temp = arr[min_idx];
        arr[min_idx] = arr[i];
        arr[i] = temp;
    }
}

void heapify(int arr[], int n, int i) {
    int largest = i;
    int l = 2*i + 1;
    int r = 2*i + 2;
    if (l < n && arr[l] > arr[largest]) {
        largest = l;
    }
    if (r < n && arr[r] > arr[largest]) {
        largest = r;
    }
    if (largest != i) {
        int temp = arr[i];
        arr[i] = arr[largest];
        arr[largest] = temp;
        heapify(arr, n, largest);
    }
}

void heapSort(int arr[], int n) {
    for (int i = n/2 - 1; i >= 0; i--) {
        heapify(arr, n, i);
    }
    for (int i = n-1; i >= 0; i--) {
        int temp = arr[0];
        arr[0] = arr[i];
        arr[i] = temp;
        heapify(arr, i, 0);
    }
}

void merge(int arr[], int l, int m, int r) {
    int i, j, k;
    int n1 = m - l + 1;
    int n2 = r - m;
    int L[n1], R[n2];
    for (i = 0; i < n1; i++) {
        L[i] = arr[l + i];
    }
    for (j = 0; j < n2; j++) {
        R[j] = arr[m + 1+ j];
    }
    i = 0;
    j = 0;
    k = l;
    while (i < n1 && j < n2) {
        if (L[i] <= R[j]) {
            arr[k] = L[i];
            i++;
        } else {
            arr[k] = R[j];
            j++;
        }
        k++;
    }
    while (i < n1) {
        arr[k] = L[i];
        i++;
        k++;
    }
    while (j < n2) {
        arr[k] = R[j];
        j++;
        k++;
    }
}

void mergeSort(int arr[], int l, int r) {
    if (l < r) {
        int m = l+(r-l)/2;
        mergeSort(arr, l, m);
        mergeSort(arr, m+1, r);
        merge(arr, l, m, r);
    }
}

int main() {
    const int n = 30000;
    int arr1[n], arr2[n], arr3[n], arr4[n], arr5[n], arr6[n], arr7[n];
    srand(time(0));
    for (int i = 0; i < n; i++) {
        int num = rand();
        arr1[i] = num;
        arr2[i] = num;
        arr3[i] = num;
        arr4[i] = num;
        arr5[i] = num;
        arr6[i] = num;
        arr7[i] = num;
    }
    auto start = high_resolution_clock::now();
    insertionSort(arr1, n);
    auto stop = high_resolution_clock::now();
    auto duration = duration_cast<milliseconds>(stop - start);
    cout << "Insertion sort: " << duration.count() << "ms" << endl;
    start = high_resolution_clock::now();
    shellSort(arr2, n);
    stop = high_resolution_clock::now();
    duration = duration_cast<milliseconds>(stop - start);
    cout << "Shell sort: " << duration.count() << "ms" << endl;
    start = high_resolution_clock::now();
    bubbleSort(arr3, n);
    stop = high_resolution_clock::now();
    duration = duration_cast<milliseconds>(stop - start);
    cout << "Bubble sort: " << duration.count() << "ms" << endl;
    start = high_resolution_clock::now();
    quickSort(arr4, 0, n-1);
    stop = high_resolution_clock::now();
    duration = duration_cast<milliseconds>(stop - start);
    cout << "Quick sort: " << duration.count() << "ms" << endl;
    start = high_resolution_clock::now();
    selectionSort(arr5, n);
    stop = high_resolution_clock::now();
    duration = duration_cast<milliseconds>(stop - start);
    cout << "Selection sort: " << duration.count() << "ms" << endl;
    start = high_resolution_clock::now();
    heapSort(arr6, n);
    stop = high_resolution_clock::now();
    duration = duration_cast<milliseconds>(stop - start);
    cout << "Heap sort: " << duration.count() << "ms" << endl;
    start = high_resolution_clock::now();
    mergeSort(arr7, 0, n-1);
    stop = high_resolution_clock::now();
    duration = duration_cast<milliseconds>(stop - start);
    cout << "Merge sort: " << duration.count() << "ms" << endl;
    return 0;
}

注意：以上代码中，使用了C++11的chrono库，它可以用来测量程序的运行时间。如果你使用的是旧版C++，则需要使用其他方式来测量运行时间。