Here's some simple code that prints all the C(n,m) combinations. It works by initializing and moving a set of array indices that point to next valid combination. The indices are initialized to point to the lowest m indices (lexicographically the smallest combination). Then on, starting with the m-th index, we try to move the indices forward. if an index has reached its limit, we try the previous index (all the way down to index 1). If we can move an index forward, then we reset all greater indices.

m=(rand()%n)+1; // m will vary from 1 to n

for (i=0;i<n;i++) a[i]=i+1;

// we want to print all possible C(n,m) combinations of selecting m objects out of n
printf("Printing C(%d,%d) possible combinations ...\n", n,m);

// This is an adhoc algo that keeps m pointers to the next valid combination
for (i=0;i<m;i++) p[i]=i; // the p[.] contain indices to the a vector whose elements constitute next combination

done=false;
while (!done)
{
    // print combination
    for (i=0;i<m;i++) printf("%2d ", a[p[i]]);
    printf("\n");

    // update combination
    // method: start with p[m-1]. try to increment it. if it is already at the end, then try moving p[m-2] ahead.
    // if this is possible, then reset p[m-1] to 1 more than (the new) p[m-2].
    // if p[m-2] can not also be moved, then try p[m-3]. move that ahead. then reset p[m-2] and p[m-1].
    // repeat all the way down to p[0]. if p[0] can not also be moved, then we have generated all combinations.
    j=m-1;
    i=1;
    move_found=false;
    while ((j>=0) && !move_found)
    {
        if (p[j]<(n-i)) 
        {
            move_found=true;
            p[j]++; // point p[j] to next index
            for (k=j+1;k<m;k++)
            {
                p[k]=p[j]+(k-j);
            }
        }
        else
        {
            j--;
            i++;
        }
    }
    if (!move_found) done=true;
}

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;
}

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' ]
]

Here's some simple code that prints all the C(n,m) combinations. It works by initializing and moving a set of array indices that point to next valid combination. The indices are initialized to point to the lowest m indices (lexicographically the smallest combination). Then on, starting with the m-th index, we try to move the indices forward. if an index has reached its limit, we try the previous index (all the way down to index 1). If we can move an index forward, then we reset all greater indices.

m=(rand()%n)+1; // m will vary from 1 to n

for (i=0;i<n;i++) a[i]=i+1;

// we want to print all possible C(n,m) combinations of selecting m objects out of n
printf("Printing C(%d,%d) possible combinations ...\n", n,m);

// This is an adhoc algo that keeps m pointers to the next valid combination
for (i=0;i<m;i++) p[i]=i; // the p[.] contain indices to the a vector whose elements constitute next combination

done=false;
while (!done)
{
    // print combination
    for (i=0;i<m;i++) printf("%2d ", a[p[i]]);
    printf("\n");

    // update combination
    // method: start with p[m-1]. try to increment it. if it is already at the end, then try moving p[m-2] ahead.
    // if this is possible, then reset p[m-1] to 1 more than (the new) p[m-2].
    // if p[m-2] can not also be moved, then try p[m-3]. move that ahead. then reset p[m-2] and p[m-1].
    // repeat all the way down to p[0]. if p[0] can not also be moved, then we have generated all combinations.
    j=m-1;
    i=1;
    move_found=false;
    while ((j>=0) && !move_found)
    {
        if (p[j]<(n-i)) 
        {
            move_found=true;
            p[j]++; // point p[j] to next index
            for (k=j+1;k<m;k++)
            {
                p[k]=p[j]+(k-j);
            }
        }
        else
        {
            j--;
            i++;
        }
    }
    if (!move_found) done=true;
}

这是一个优雅的Scala通用实现，如99个Scala问题所述。

object P26 {
  def flatMapSublists[A,B](ls: List[A])(f: (List[A]) => List[B]): List[B] = 
    ls match {
      case Nil => Nil
      case sublist@(_ :: tail) => f(sublist) ::: flatMapSublists(tail)(f)
    }

  def combinations[A](n: Int, ls: List[A]): List[List[A]] =
    if (n == 0) List(Nil)
    else flatMapSublists(ls) { sl =>
      combinations(n - 1, sl.tail) map {sl.head :: _}
    }
}

如果你可以使用SQL语法——比如，如果你使用LINQ访问一个结构或数组的字段，或者直接访问一个数据库，其中有一个名为“Alphabet”的表，只有一个字符字段“Letter”，你可以适应以下代码:

SELECT A.Letter, B.Letter, C.Letter
FROM Alphabet AS A, Alphabet AS B, Alphabet AS C
WHERE A.Letter<>B.Letter AND A.Letter<>C.Letter AND B.Letter<>C.Letter
AND A.Letter<B.Letter AND B.Letter<C.Letter

这将返回所有3个字母的组合，不管你在表格“字母表”中有多少个字母(它可以是3,8,10,27等)。

如果你想要的是所有的排列，而不是组合(也就是说，你想要“ACB”和“ABC”被视为不同的，而不是只出现一次)，只需删除最后一行(and一行)，就完成了。

Post-Edit:重新阅读问题后，我意识到需要的是通用算法，而不仅仅是选择3个项目的特定算法。Adam Hughes的答案是完整的，不幸的是我还不能投票。这个答案很简单，但只适用于你想要三样东西的时候。