假设你的字母数组是这样的:"ABCDEFGH"。你有三个下标(i, j, k)来表示你要用哪个字母来表示当前单词。

A B C D E F G H
^ ^ ^
i j k

首先你改变k，所以下一步看起来像这样:

A B C D E F G H
^ ^   ^
i j   k

如果你到达终点，你继续改变j和k。

A B C D E F G H
^   ^ ^
i   j k

A B C D E F G H
^   ^   ^
i   j   k

一旦j达到G, i也开始变化。

A B C D E F G H
  ^ ^ ^
  i j k

A B C D E F G H
  ^ ^   ^
  i j   k
...

用代码写出来是这样的

void print_combinations(const char *string)
{
    int i, j, k;
    int len = strlen(string);

    for (i = 0; i < len - 2; i++)
    {
        for (j = i + 1; j < len - 1; j++)
        {
            for (k = j + 1; k < len; k++)
                printf("%c%c%c\n", string[i], string[j], string[k]);
        }
    }
}

下面是一个使用宏的Lisp方法。这适用于Common Lisp，也适用于其他Lisp方言。

下面的代码创建了'n'个嵌套循环，并为列表lst中的'n'个元素的每个组合执行任意代码块(存储在body变量中)。变量var指向一个包含用于循环的变量的列表。

(defmacro do-combinations ((var lst num) &body body)
  (loop with syms = (loop repeat num collect (gensym))
        for i on syms
        for k = `(loop for ,(car i) on (cdr ,(cadr i))
                         do (let ((,var (list ,@(reverse syms)))) (progn ,@body)))
                then `(loop for ,(car i) on ,(if (cadr i) `(cdr ,(cadr i)) lst) do ,k)
        finally (return k)))

让我们看看…

(macroexpand-1 '(do-combinations (p '(1 2 3 4 5 6 7) 4) (pprint (mapcar #'car p))))

(LOOP FOR #:G3217 ON '(1 2 3 4 5 6 7) DO
 (LOOP FOR #:G3216 ON (CDR #:G3217) DO
  (LOOP FOR #:G3215 ON (CDR #:G3216) DO
   (LOOP FOR #:G3214 ON (CDR #:G3215) DO
    (LET ((P (LIST #:G3217 #:G3216 #:G3215 #:G3214)))
     (PROGN (PPRINT (MAPCAR #'CAR P))))))))

(do-combinations (p '(1 2 3 4 5 6 7) 4) (pprint (mapcar #'car p)))

(1 2 3 4)
(1 2 3 5)
(1 2 3 6)
...

由于默认情况下不存储组合，因此存储空间保持在最小值。选择主体代码而不是存储所有结果的可能性也提供了更大的灵活性。

这里你有一个用c#编写的该算法的惰性评估版本:

    static bool nextCombination(int[] num, int n, int k)
    {
        bool finished, changed;

        changed = finished = false;

        if (k > 0)
        {
            for (int i = k - 1; !finished && !changed; i--)
            {
                if (num[i] < (n - 1) - (k - 1) + i)
                {
                    num[i]++;
                    if (i < k - 1)
                    {
                        for (int j = i + 1; j < k; j++)
                        {
                            num[j] = num[j - 1] + 1;
                        }
                    }
                    changed = true;
                }
                finished = (i == 0);
            }
        }

        return changed;
    }

    static IEnumerable Combinations<T>(IEnumerable<T> elements, int k)
    {
        T[] elem = elements.ToArray();
        int size = elem.Length;

        if (k <= size)
        {
            int[] numbers = new int[k];
            for (int i = 0; i < k; i++)
            {
                numbers[i] = i;
            }

            do
            {
                yield return numbers.Select(n => elem[n]);
            }
            while (nextCombination(numbers, size, k));
        }
    }

及测试部分:

    static void Main(string[] args)
    {
        int k = 3;
        var t = new[] { "dog", "cat", "mouse", "zebra"};

        foreach (IEnumerable<string> i in Combinations(t, k))
        {
            Console.WriteLine(string.Join(",", i));
        }
    }

希望这对你有帮助!

另一种版本，迫使所有前k个组合首先出现，然后是所有前k+1个组合，然后是所有前k+2个组合，等等。这意味着如果你对数组进行排序，最重要的在最上面，它会把它们逐渐扩展到下一个——只有在必须这样做的时候。

private static bool NextCombinationFirstsAlwaysFirst(int[] num, int n, int k)
{
    if (k > 1 && NextCombinationFirstsAlwaysFirst(num, num[k - 1], k - 1))
        return true;

    if (num[k - 1] + 1 == n)
        return false;

    ++num[k - 1];
    for (int i = 0; i < k - 1; ++i)
        num[i] = i;

    return true;
}

例如，如果你在k=3, n=5上运行第一个方法("nextCombination")，你会得到:

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

但如果你跑

int[] nums = new int[k];
for (int i = 0; i < k; ++i)
    nums[i] = i;
do
{
    Console.WriteLine(string.Join(" ", nums));
}
while (NextCombinationFirstsAlwaysFirst(nums, n, k));

你会得到这个(为了清晰起见，我添加了空行):

0 1 2

0 1 3
0 2 3
1 2 3

0 1 4
0 2 4
1 2 4
0 3 4
1 3 4
2 3 4

它只在必须添加时才添加“4”，而且在添加“4”之后，它只在必须添加时再添加“3”(在执行01、02、12之后)。

我发现这个线程很有用，我想我会添加一个Javascript解决方案，你可以弹出到Firebug。取决于你的JS引擎，如果起始字符串很大，可能会花一点时间。

function string_recurse(active, rest) {
    if (rest.length == 0) {
        console.log(active);
    } else {
        string_recurse(active + rest.charAt(0), rest.substring(1, rest.length));
        string_recurse(active, rest.substring(1, rest.length));
    }
}
string_recurse("", "abc");

输出如下:

abc
ab
ac
a
bc
b
c

这个答案怎么样……这将打印所有长度为3的组合…它可以推广到任何长度… 工作代码…

#include<iostream>
#include<string>
using namespace std;

void combination(string a,string dest){
int l = dest.length();
if(a.empty() && l  == 3 ){
 cout<<dest<<endl;}
else{
  if(!a.empty() && dest.length() < 3 ){
     combination(a.substr(1,a.length()),dest+a[0]);}
  if(!a.empty() && dest.length() <= 3 ){
      combination(a.substr(1,a.length()),dest);}
 }

 }

 int main(){
 string demo("abcd");
 combination(demo,"");
 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' ]
]