这是我对javascript的贡献(没有递归)

set = ["q0", "q1", "q2", "q3"]
collector = []


function comb(num) {
  results = []
  one_comb = []
  for (i = set.length - 1; i >= 0; --i) {
    tmp = Math.pow(2, i)
    quotient = parseInt(num / tmp)
    results.push(quotient)
    num = num % tmp
  }
  k = 0
  for (i = 0; i < results.length; ++i)
    if (results[i]) {
      ++k
      one_comb.push(set[i])
    }
  if (collector[k] == undefined)
    collector[k] = []
  collector[k].push(one_comb)
}


sum = 0
for (i = 0; i < set.length; ++i)
  sum += Math.pow(2, i)
 for (ii = sum; ii > 0; --ii)
  comb(ii)
 cnt = 0
for (i = 1; i < collector.length; ++i) {
  n = 0
  for (j = 0; j < collector[i].length; ++j)
    document.write(++cnt, " - " + (++n) + " - ", collector[i][j], "<br>")
  document.write("<hr>")
}   

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' ]
]

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);

static IEnumerable<string> Combinations(List<string> characters, int length)
{
    for (int i = 0; i < characters.Count; i++)
    {
        // only want 1 character, just return this one
        if (length == 1)
            yield return characters[i];

        // want more than one character, return this one plus all combinations one shorter
        // only use characters after the current one for the rest of the combinations
        else
            foreach (string next in Combinations(characters.GetRange(i + 1, characters.Count - (i + 1)), length - 1))
                yield return characters[i] + next;
    }
}

作为迭代器对象实现的MetaTrader MQL4非常快速的组合。

代码很容易理解。

我对很多算法进行了基准测试，这个算法真的非常快——大约比大多数next_combination()函数快3倍。

class CombinationsIterator { private: int input_array[]; // 1 2 3 4 5 int index_array[]; // i j k int m_elements; // N int m_indices; // K public: CombinationsIterator(int &src_data[], int k) { m_indices = k; m_elements = ArraySize(src_data); ArrayCopy(input_array, src_data); ArrayResize(index_array, m_indices); // create initial combination (0..k-1) for (int i = 0; i < m_indices; i++) { index_array[i] = i; } } // https://stackoverflow.com/questions/5076695 // bool next_combination(int &item[], int k, int N) bool advance() { int N = m_elements; for (int i = m_indices - 1; i >= 0; --i) { if (index_array[i] < --N) { ++index_array[i]; for (int j = i + 1; j < m_indices; ++j) { index_array[j] = index_array[j - 1] + 1; } return true; } } return false; } void getItems(int &items[]) { // fill items[] from input array for (int i = 0; i < m_indices; i++) { items[i] = input_array[index_array[i]]; } } };

测试上述迭代器类的驱动程序:

//+------------------------------------------------------------------+ //| | //+------------------------------------------------------------------+ // driver program to test above class #define N 5 #define K 3 void OnStart() { int myset[N] = {1, 2, 3, 4, 5}; int items[K]; CombinationsIterator comboIt(myset, K); do { comboIt.getItems(items); printf("%s", ArrayToString(items)); } while (comboIt.advance()); }

输出: 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

Python中的简短示例:

def comb(sofar, rest, n):
    if n == 0:
        print sofar
    else:
        for i in range(len(rest)):
            comb(sofar + rest[i], rest[i+1:], n-1)

>>> comb("", "abcde", 3)
abc
abd
abe
acd
ace
ade
bcd
bce
bde
cde

为了解释，递归方法用下面的例子描述:

示例:A B C D E 3的所有组合是:

A与其余2的所有组合(B C D E) B与其余2的所有组合(C D E) C与其余2的所有组合(D E)