用c#的另一个解决方案:

 static List<List<T>> GetCombinations<T>(List<T> originalItems, int combinationLength)
    {
        if (combinationLength < 1)
        {
            return null;
        }

        return CreateCombinations<T>(new List<T>(), 0, combinationLength, originalItems);
    }

 static List<List<T>> CreateCombinations<T>(List<T> initialCombination, int startIndex, int length, List<T> originalItems)
    {
        List<List<T>> combinations = new List<List<T>>();
        for (int i = startIndex; i < originalItems.Count - length + 1; i++)
        {
            List<T> newCombination = new List<T>(initialCombination);
            newCombination.Add(originalItems[i]);
            if (length > 1)
            {
                List<List<T>> newCombinations = CreateCombinations(newCombination, i + 1, length - 1, originalItems);
                combinations.AddRange(newCombinations);
            }
            else
            {
                combinations.Add(newCombination);
            }
        }

        return combinations;
    }

用法示例:

   List<char> initialArray = new List<char>() { 'a','b','c','d'};
   int combinationLength = 3;
   List<List<char>> combinations = GetCombinations(initialArray, combinationLength);

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。

Lisp宏为所有值r(每次取)生成代码

(defmacro txaat (some-list taken-at-a-time)
  (let* ((vars (reverse (truncate-list '(a b c d e f g h i j) taken-at-a-time))))
    `(
      ,@(loop for i below taken-at-a-time 
           for j in vars 
           with nested = nil 
           finally (return nested) 
           do
             (setf 
              nested 
              `(loop for ,j from
                    ,(if (< i (1- (length vars)))
                         `(1+ ,(nth (1+ i) vars))
                         0)
                  below (- (length ,some-list) ,i)
                    ,@(if (equal i 0) 
                          `(collect 
                               (list
                                ,@(loop for k from (1- taken-at-a-time) downto 0
                                     append `((nth ,(nth k vars) ,some-list)))))
                          `(append ,nested))))))))

So,

CL-USER> (macroexpand-1 '(txaat '(a b c d) 1))
(LOOP FOR A FROM 0 TO (- (LENGTH '(A B C D)) 1)
    COLLECT (LIST (NTH A '(A B C D))))
T
CL-USER> (macroexpand-1 '(txaat '(a b c d) 2))
(LOOP FOR A FROM 0 TO (- (LENGTH '(A B C D)) 2)
      APPEND (LOOP FOR B FROM (1+ A) TO (- (LENGTH '(A B C D)) 1)
                   COLLECT (LIST (NTH A '(A B C D)) (NTH B '(A B C D)))))
T
CL-USER> (macroexpand-1 '(txaat '(a b c d) 3))
(LOOP FOR A FROM 0 TO (- (LENGTH '(A B C D)) 3)
      APPEND (LOOP FOR B FROM (1+ A) TO (- (LENGTH '(A B C D)) 2)
                   APPEND (LOOP FOR C FROM (1+ B) TO (- (LENGTH '(A B C D)) 1)
                                COLLECT (LIST (NTH A '(A B C D))
                                              (NTH B '(A B C D))
                                              (NTH C '(A B C D))))))
T

CL-USER> 

And,

CL-USER> (txaat '(a b c d) 1)
((A) (B) (C) (D))
CL-USER> (txaat '(a b c d) 2)
((A B) (A C) (A D) (B C) (B D) (C D))
CL-USER> (txaat '(a b c d) 3)
((A B C) (A B D) (A C D) (B C D))
CL-USER> (txaat '(a b c d) 4)
((A B C D))
CL-USER> (txaat '(a b c d) 5)
NIL
CL-USER> (txaat '(a b c d) 0)
NIL
CL-USER> 

简短的java解决方案:

import java.util.Arrays;

public class Combination {
    public static void main(String[] args){
        String[] arr = {"A","B","C","D","E","F"};
        combinations2(arr, 3, 0, new String[3]);
    }

    static void combinations2(String[] arr, int len, int startPosition, String[] result){
        if (len == 0){
            System.out.println(Arrays.toString(result));
            return;
        }       
        for (int i = startPosition; i <= arr.length-len; i++){
            result[result.length - len] = arr[i];
            combinations2(arr, len-1, i+1, result);
        }
    }       
}

结果将是

[A, B, C]
[A, B, D]
[A, B, E]
[A, B, F]
[A, C, D]
[A, C, E]
[A, C, F]
[A, D, E]
[A, D, F]
[A, E, F]
[B, C, D]
[B, C, E]
[B, C, F]
[B, D, E]
[B, D, F]
[B, E, F]
[C, D, E]
[C, D, F]
[C, E, F]
[D, E, F]

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' ]
]

我已经编写了一个类来处理处理二项式系数的常见函数，这是您的问题属于的问题类型。它执行以下任务:

Outputs all the K-indexes in a nice format for any N choose K to a file. The K-indexes can be substituted with more descriptive strings or letters. This method makes solving this type of problem quite trivial. Converts the K-indexes to the proper index of an entry in the sorted binomial coefficient table. This technique is much faster than older published techniques that rely on iteration. It does this by using a mathematical property inherent in Pascal's Triangle. My paper talks about this. I believe I am the first to discover and publish this technique, but I could be wrong. Converts the index in a sorted binomial coefficient table to the corresponding K-indexes. Uses Mark Dominus method to calculate the binomial coefficient, which is much less likely to overflow and works with larger numbers. The class is written in .NET C# and provides a way to manage the objects related to the problem (if any) by using a generic list. The constructor of this class takes a bool value called InitTable that when true will create a generic list to hold the objects to be managed. If this value is false, then it will not create the table. The table does not need to be created in order to perform the 4 above methods. Accessor methods are provided to access the table. There is an associated test class which shows how to use the class and its methods. It has been extensively tested with 2 cases and there are no known bugs.

要了解这个类并下载代码，请参见将二项式系数表化。

将这个类转换为c++应该不难。