为此，我在SQL Server 2005中创建了一个解决方案，并将其发布在我的网站上:http://www.jessemclain.com/downloads/code/sql/fn_GetMChooseNCombos.sql.htm

下面是一个例子来说明用法:

SELECT * FROM dbo.fn_GetMChooseNCombos('ABCD', 2, '')

结果:

Word
----
AB
AC
AD
BC
BD
CD

(6 row(s) affected)

还有另一个递归解决方案(你应该能够使用字母而不是数字)使用堆栈，虽然比大多数更短:

stack = [] 
def choose(n,x):
   r(0,0,n+1,x)

def r(p, c, n,x):
   if x-c == 0:
      print stack
      return

   for i in range(p, n-(x-1)+c):
      stack.append(i)
      r(i+1,c+1,n,x)
      stack.pop()

4选3或者我想要从0到4的所有3种数字组合

choose(4,3) 

[0, 1, 2]
[0, 1, 3]
[0, 1, 4]
[0, 2, 3]
[0, 2, 4]
[0, 3, 4]
[1, 2, 3]
[1, 2, 4]
[1, 3, 4]
[2, 3, 4]

简单但缓慢的c++回溯算法。

#include <iostream>

void backtrack(int* numbers, int n, int k, int i, int s)
{
    if (i == k)
    {
        for (int j = 0; j < k; ++j)
        {
            std::cout << numbers[j];
        }
        std::cout << std::endl;

        return;
    }

    if (s > n)
    {
        return;
    }

    numbers[i] = s;
    backtrack(numbers, n, k, i + 1, s + 1);
    backtrack(numbers, n, k, i, s + 1);
}

int main(int argc, char* argv[])
{
    int n = 5;
    int k = 3;

    int* numbers = new int[k];

    backtrack(numbers, n, k, 0, 1);

    delete[] numbers;

    return 0;
}

这是我想出的解决这个问题的算法。它是用c++编写的，但是可以适应几乎任何支持位操作的语言。

void r_nCr(const unsigned int &startNum, const unsigned int &bitVal, const unsigned int &testNum) // Should be called with arguments (2^r)-1, 2^(r-1), 2^(n-1)
{
    unsigned int n = (startNum - bitVal) << 1;
    n += bitVal ? 1 : 0;

    for (unsigned int i = log2(testNum) + 1; i > 0; i--) // Prints combination as a series of 1s and 0s
        cout << (n >> (i - 1) & 1);
    cout << endl;

    if (!(n & testNum) && n != startNum)
        r_nCr(n, bitVal, testNum);

    if (bitVal && bitVal < testNum)
        r_nCr(startNum, bitVal >> 1, testNum);
}

你可以在这里看到它如何工作的解释。

在Python中，利用递归的优势和所有事情都是通过引用完成的事实。对于非常大的集合，这将占用大量内存，但其优点是初始集合可以是一个复杂的对象。它只会找到唯一的组合。

import copy

def find_combinations( length, set, combinations = None, candidate = None ):
    # recursive function to calculate all unique combinations of unique values
    # from [set], given combinations of [length].  The result is populated
    # into the 'combinations' list.
    #
    if combinations == None:
        combinations = []
    if candidate == None:
        candidate = []

    for item in set:
        if item in candidate:
            # this item already appears in the current combination somewhere.
            # skip it
            continue

        attempt = copy.deepcopy(candidate)
        attempt.append(item)
        # sorting the subset is what gives us completely unique combinations,
        # so that [1, 2, 3] and [1, 3, 2] will be treated as equals
        attempt.sort()

        if len(attempt) < length:
            # the current attempt at finding a new combination is still too
            # short, so add another item to the end of the set
            # yay recursion!
            find_combinations( length, set, combinations, attempt )
        else:
            # the current combination attempt is the right length.  If it
            # already appears in the list of found combinations then we'll
            # skip it.
            if attempt in combinations:
                continue
            else:
                # otherwise, we append it to the list of found combinations
                # and move on.
                combinations.append(attempt)
                continue
    return len(combinations)

你可以这样使用它。传递'result'是可选的，所以你可以用它来获取可能组合的数量…尽管这样做效率很低(最好通过计算来完成)。

size = 3
set = [1, 2, 3, 4, 5]
result = []

num = find_combinations( size, set, result ) 
print "size %d results in %d sets" % (size, num)
print "result: %s" % (result,)

您应该从测试数据中得到以下输出:

size 3 results in 10 sets
result: [[1, 2, 3], [1, 2, 4], [1, 2, 5], [1, 3, 4], [1, 3, 5], [1, 4, 5], [2, 3, 4], [2, 3, 5], [2, 4, 5], [3, 4, 5]]

如果你的集合是这样的，它也会工作得很好:

set = [
    [ 'vanilla', 'cupcake' ],
    [ 'chocolate', 'pudding' ],
    [ 'vanilla', 'pudding' ],
    [ 'chocolate', 'cookie' ],
    [ 'mint', 'cookie' ]
]

短快C实现

#include <stdio.h>

void main(int argc, char *argv[]) {
  const int n = 6; /* The size of the set; for {1, 2, 3, 4} it's 4 */
  const int p = 4; /* The size of the subsets; for {1, 2}, {1, 3}, ... it's 2 */
  int comb[40] = {0}; /* comb[i] is the index of the i-th element in the combination */

  int i = 0;
  for (int j = 0; j <= n; j++) comb[j] = 0;
  while (i >= 0) {
    if (comb[i] < n + i - p + 1) {
       comb[i]++;
       if (i == p - 1) { for (int j = 0; j < p; j++) printf("%d ", comb[j]); printf("\n"); }
       else            { comb[++i] = comb[i - 1]; }
    } else i--; }
}

要查看它有多快，请使用这段代码并测试它

#include <time.h>
#include <stdio.h>

void main(int argc, char *argv[]) {
  const int n = 32; /* The size of the set; for {1, 2, 3, 4} it's 4 */
  const int p = 16; /* The size of the subsets; for {1, 2}, {1, 3}, ... it's 2 */
  int comb[40] = {0}; /* comb[i] is the index of the i-th element in the combination */

  int c = 0; int i = 0;
  for (int j = 0; j <= n; j++) comb[j] = 0;
  while (i >= 0) {
    if (comb[i] < n + i - p + 1) {
       comb[i]++;
       /* if (i == p - 1) { for (int j = 0; j < p; j++) printf("%d ", comb[j]); printf("\n"); } */
       if (i == p - 1) c++;
       else            { comb[++i] = comb[i - 1]; }
    } else i--; }
  printf("%d!%d == %d combination(s) in %15.3f second(s)\n ", p, n, c, clock()/1000.0);
}

使用cmd.exe (windows)测试:

Microsoft Windows XP [Version 5.1.2600]
(C) Copyright 1985-2001 Microsoft Corp.

c:\Program Files\lcc\projects>combination
16!32 == 601080390 combination(s) in          5.781 second(s)

c:\Program Files\lcc\projects>

祝你有愉快的一天。