你可以使用Asif算法来生成所有可能的组合。这可能是最简单和最有效的方法。你可以在这里查看媒体文章。

让我们看看JavaScript中的实现。

function Combinations( arr, r ) {
    // To avoid object referencing, cloning the array.
    arr = arr && arr.slice() || [];

    var len = arr.length;

    if( !len || r > len || !r )
        return [ [] ];
    else if( r === len ) 
        return [ arr ];

    if( r === len ) return arr.reduce( ( x, v ) => {
        x.push( [ v ] );

        return x;
    }, [] );

    var head = arr.shift();

    return Combinations( arr, r - 1 ).map( x => {
        x.unshift( head );

        return x;
    } ).concat( Combinations( arr, r ) );
}

// Now do your stuff.

console.log( Combinations( [ 'a', 'b', 'c', 'd', 'e' ], 3 ) );

c#简单算法。 (我发布它是因为我试图使用你们上传的那个，但由于某种原因我无法编译它——扩展一个类?所以我自己写了一个，以防别人遇到和我一样的问题)。 顺便说一下，除了基本的编程，我对c#没什么兴趣，但是这个工作得很好。

public static List<List<int>> GetSubsetsOfSizeK(List<int> lInputSet, int k)
        {
            List<List<int>> lSubsets = new List<List<int>>();
            GetSubsetsOfSizeK_rec(lInputSet, k, 0, new List<int>(), lSubsets);
            return lSubsets;
        }

public static void GetSubsetsOfSizeK_rec(List<int> lInputSet, int k, int i, List<int> lCurrSet, List<List<int>> lSubsets)
        {
            if (lCurrSet.Count == k)
            {
                lSubsets.Add(lCurrSet);
                return;
            }

            if (i >= lInputSet.Count)
                return;

            List<int> lWith = new List<int>(lCurrSet);
            List<int> lWithout = new List<int>(lCurrSet);
            lWith.Add(lInputSet[i++]);

            GetSubsetsOfSizeK_rec(lInputSet, k, i, lWith, lSubsets);
            GetSubsetsOfSizeK_rec(lInputSet, k, i, lWithout, lSubsets);
        }

GetSubsetsOfSizeK(set of type List<int>， integer k)

您可以修改它以遍历您正在处理的任何内容。

好运！

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)

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' ]
]

这是一个为nCk生成组合的递归程序。假设集合中的元素从1到n

#include<stdio.h>
#include<stdlib.h>

int nCk(int n,int loopno,int ini,int *a,int k)
{
    static int count=0;
    int i;
    loopno--;
    if(loopno<0)
    {
        a[k-1]=ini;
        for(i=0;i<k;i++)
        {
            printf("%d,",a[i]);
        }
        printf("\n");
        count++;
        return 0;
    }
    for(i=ini;i<=n-loopno-1;i++)
    {
        a[k-1-loopno]=i+1;
        nCk(n,loopno,i+1,a,k);
    }
    if(ini==0)
    return count;
    else
    return 0;
}

void main()
{
    int n,k,*a,count;
    printf("Enter the value of n and k\n");
    scanf("%d %d",&n,&k);
    a=(int*)malloc(k*sizeof(int));
    count=nCk(n,k,0,a,k);
    printf("No of combinations=%d\n",count);
}

下面的递归算法从有序集中选取所有k元素组合:

选择组合中的第一个元素I 将I与从大于I的元素集中递归选择的k-1个元素的组合组合。

对集合中的每一个i进行上述迭代。

为了避免重复，您必须选择比i大的其余元素。这样[3,5]将只被选中一次，即[3]与[5]结合，而不是两次(该条件消除了[5]+[3])。没有这个条件，你得到的是变化而不是组合。