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)

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 ) );

一个简洁的Javascript解决方案:

Array.prototype.combine=function combine(k){    
    var toCombine=this;
    var last;
    function combi(n,comb){             
        var combs=[];
        for ( var x=0,y=comb.length;x<y;x++){
            for ( var l=0,m=toCombine.length;l<m;l++){      
                combs.push(comb[x]+toCombine[l]);           
            }
        }
        if (n<k-1){
            n++;
            combi(n,combs);
        } else{last=combs;}
    }
    combi(1,toCombine);
    return last;
}
// Example:
// var toCombine=['a','b','c'];
// var results=toCombine.combine(4);

下面是c++中的迭代算法，它不使用STL，也不使用递归，也不使用条件嵌套循环。这样更快，它不执行任何元素交换，也不会给堆栈带来递归负担，还可以通过分别用mallloc()、free()和printf()替换new、delete和std::cout轻松地移植到ANSI C。

如果你想用不同或更长的字母显示元素，那么改变*字母参数以指向不同于"abcdefg"的字符串。

void OutputArrayChar(unsigned int* ka, size_t n, const char *alphabet) {
    for (int i = 0; i < n; i++)
        std::cout << alphabet[ka[i]] << ",";
    std::cout << endl;
}
    

void GenCombinations(const unsigned int N, const unsigned int K, const char *alphabet) {
    unsigned int *ka = new unsigned int [K];  //dynamically allocate an array of UINTs
    unsigned int ki = K-1;                    //Point ki to the last elemet of the array
    ka[ki] = N-1;                             //Prime the last elemet of the array.
    
    while (true) {
        unsigned int tmp = ka[ki];  //Optimization to prevent reading ka[ki] repeatedly

        while (ki)                  //Fill to the left with consecutive descending values (blue squares)
            ka[--ki] = --tmp;
        OutputArrayChar(ka, K, alphabet);
    
        while (--ka[ki] == ki) {    //Decrement and check if the resulting value equals the index (bright green squares)
            OutputArrayChar(ka, K, alphabet);
            if (++ki == K) {      //Exit condition (all of the values in the array are flush to the left)
                delete[] ka;
                return;
            }                   
        }
    }
}
    

int main(int argc, char *argv[])
{
    GenCombinations(7, 4, "abcdefg");
    return 0;
}

重要提示:字母参数*必须指向至少N个字符的字符串。你也可以传递一个在其他地方定义的字符串地址。

组合:从“7选4”中选择。

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' ]
]

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)