我有一个用于project euler的排列算法，用python编写:

def missing(miss,src):
    "Returns the list of items in src not present in miss"
    return [i for i in src if i not in miss]


def permutation_gen(n,l):
    "Generates all the permutations of n items of the l list"
    for i in l:
        if n<=1: yield [i]
        r = [i]
        for j in permutation_gen(n-1,missing([i],l)):  yield r+j

If

n<len(l) 

你应该有所有你需要的组合，没有重复，你需要吗?

它是一个生成器，所以你可以这样使用它:

for comb in permutation_gen(3,list("ABCDEFGH")):
    print comb 

在VB。Net，该算法从一组数字(PoolArray)中收集n个数字的所有组合。例如，从“8,10,20,33,41,44,47”中选择5个选项的所有组合。

Sub CreateAllCombinationsOfPicksFromPool(ByVal PicksArray() As UInteger, ByVal PicksIndex As UInteger, ByVal PoolArray() As UInteger, ByVal PoolIndex As UInteger)
    If PicksIndex < PicksArray.Length Then
        For i As Integer = PoolIndex To PoolArray.Length - PicksArray.Length + PicksIndex
            PicksArray(PicksIndex) = PoolArray(i)
            CreateAllCombinationsOfPicksFromPool(PicksArray, PicksIndex + 1, PoolArray, i + 1)
        Next
    Else
        ' completed combination. build your collections using PicksArray.
    End If
End Sub

        Dim PoolArray() As UInteger = Array.ConvertAll("8,10,20,33,41,44,47".Split(","), Function(u) UInteger.Parse(u))
        Dim nPicks as UInteger = 5
        Dim Picks(nPicks - 1) As UInteger
        CreateAllCombinationsOfPicksFromPool(Picks, 0, PoolArray, 0)

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;
}

下面是我的Scala解决方案:

def combinations[A](s: List[A], k: Int): List[List[A]] = 
  if (k > s.length) Nil
  else if (k == 1) s.map(List(_))
  else combinations(s.tail, k - 1).map(s.head :: _) ::: combinations(s.tail, k)

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' ]
]

说了这么多，做了这么多，这就是奥卡姆的代码。 算法是显而易见的代码..

let combi n lst =
    let rec comb l c =
        if( List.length c = n) then [c] else
        match l with
        [] -> []
        | (h::t) -> (combi t (h::c))@(combi t c)
    in
        combi lst []
;;