下面是一个方法，它从一个随机长度的字符串中给出指定大小的所有组合。类似于昆玛斯的解，但适用于不同的输入和k。

代码可以更改为换行，即'dab'从输入'abcd' w k=3。

public void run(String data, int howMany){
    choose(data, howMany, new StringBuffer(), 0);
}


//n choose k
private void choose(String data, int k, StringBuffer result, int startIndex){
    if (result.length()==k){
        System.out.println(result.toString());
        return;
    }

    for (int i=startIndex; i<data.length(); i++){
        result.append(data.charAt(i));
        choose(data,k,result, i+1);
        result.setLength(result.length()-1);
    }
}

"abcde"的输出:

ABC abd ace ade BCD bce bde cde

我们可以用比特的概念来做这个。假设我们有一个字符串“abc”，我们想要所有长度为2的元素的组合(即“ab”，“ac”，“bc”)。

我们可以在1到2^n(排他性)的数字中找到集合位。这里是1到7，只要我们设置了bits = 2，我们就可以从string中输出相应的值。

例如:

1 - 001 二零零一 3011 ->印刷ab (str[0]， str[1]) 四到一百。 5 - 101 ->打印ac (str[0]， str[2]) 6 - 110 ->印刷ab (str[1]， str[2]) 7 - 111。

代码示例:

public class StringCombinationK {   
    static void combk(String s , int k){
        int n = s.length();
        int num = 1<<n;
        int j=0;
        int count=0;

        for(int i=0;i<num;i++){
            if (countSet(i)==k){
                setBits(i,j,s);
                count++;
                System.out.println();
            }
        }

        System.out.println(count);
    }

    static void setBits(int i,int j,String s){ // print the corresponding string value,j represent the index of set bit
        if(i==0){
            return;
        }

        if(i%2==1){
            System.out.print(s.charAt(j));                  
        }

        setBits(i/2,j+1,s);
    }

    static int countSet(int i){ //count number of set bits
        if( i==0){
            return 0;
        }

        return (i%2==0? 0:1) + countSet(i/2);
    }

    public static void main(String[] arhs){
        String s = "abcdefgh";
        int k=3;
        combk(s,k);
    }
}

遵循Haskell代码同时计算组合数和组合，由于Haskell的惰性，您可以得到其中的一部分而无需计算另一部分。

import Data.Semigroup
import Data.Monoid

data Comb = MkComb {count :: Int, combinations :: [[Int]]} deriving (Show, Eq, Ord)

instance Semigroup Comb where
    (MkComb c1 cs1) <> (MkComb c2 cs2) = MkComb (c1 + c2) (cs1 ++ cs2)

instance Monoid Comb where
    mempty = MkComb 0 []

addElem :: Comb -> Int -> Comb
addElem (MkComb c cs) x = MkComb c (map (x :) cs)

comb :: Int -> Int -> Comb
comb n k | n < 0 || k < 0 = error "error in `comb n k`, n and k should be natural number"
comb n k | k == 0 || k == n = MkComb 1 [(take k [k-1,k-2..0])]
comb n k | n < k = mempty
comb n k = comb (n-1) k <> (comb (n-1) (k-1) `addElem` (n-1))

它是这样工作的:

*Main> comb 0 1
MkComb {count = 0, combinations = []}

*Main> comb 0 0
MkComb {count = 1, combinations = [[]]}

*Main> comb 1 1
MkComb {count = 1, combinations = [[0]]}

*Main> comb 4 2
MkComb {count = 6, combinations = [[1,0],[2,0],[2,1],[3,0],[3,1],[3,2]]}

*Main> count (comb 10 5)
252

另一个具有组合索引惰性生成的c#版本。这个版本维护了一个索引数组来定义所有值列表和当前组合值之间的映射，即在整个运行时不断使用O(k)额外的空间。该代码在O(k)时间内生成单个组合，包括第一个组合。

public static IEnumerable<T[]> Combinations<T>(this T[] values, int k)
{
    if (k < 0 || values.Length < k)
        yield break; // invalid parameters, no combinations possible

    // generate the initial combination indices
    var combIndices = new int[k];
    for (var i = 0; i < k; i++)
    {
        combIndices[i] = i;
    }

    while (true)
    {
        // return next combination
        var combination = new T[k];
        for (var i = 0; i < k; i++)
        {
            combination[i] = values[combIndices[i]];
        }
        yield return combination;

        // find first index to update
        var indexToUpdate = k - 1;
        while (indexToUpdate >= 0 && combIndices[indexToUpdate] >= values.Length - k + indexToUpdate)
        {
            indexToUpdate--;
        }

        if (indexToUpdate < 0)
            yield break; // done

        // update combination indices
        for (var combIndex = combIndices[indexToUpdate] + 1; indexToUpdate < k; indexToUpdate++, combIndex++)
        {
            combIndices[indexToUpdate] = combIndex;
        }
    }
}

测试代码:

foreach (var combination in new[] {'a', 'b', 'c', 'd', 'e'}.Combinations(3))
{
    System.Console.WriteLine(String.Join(" ", combination));
}

输出:

a b c
a b d
a b e
a c d
a c e
a d e
b c d
b c e
b d e
c d e

我知道这个问题已经有很多答案了，但我想在JavaScript中添加我自己的贡献，它由两个函数组成——一个生成原始n元素集的所有可能不同的k子集，另一个使用第一个函数生成原始n元素集的幂集。

下面是这两个函数的代码:

//Generate combination subsets from a base set of elements (passed as an array). This function should generate an
//array containing nCr elements, where nCr = n!/[r! (n-r)!].

//Arguments:

//[1] baseSet :     The base set to create the subsets from (e.g., ["a", "b", "c", "d", "e", "f"])
//[2] cnt :         The number of elements each subset is to contain (e.g., 3)

function MakeCombinationSubsets(baseSet, cnt)
{
    var bLen = baseSet.length;
    var indices = [];
    var subSet = [];
    var done = false;
    var result = [];        //Contains all the combination subsets generated
    var done = false;
    var i = 0;
    var idx = 0;
    var tmpIdx = 0;
    var incr = 0;
    var test = 0;
    var newIndex = 0;
    var inBounds = false;
    var tmpIndices = [];
    var checkBounds = false;

    //First, generate an array whose elements are indices into the base set ...

    for (i=0; i<cnt; i++)

        indices.push(i);

    //Now create a clone of this array, to be used in the loop itself ...

        tmpIndices = [];

        tmpIndices = tmpIndices.concat(indices);

    //Now initialise the loop ...

    idx = cnt - 1;      //point to the last element of the indices array
    incr = 0;
    done = false;
    while (!done)
    {
    //Create the current subset ...

        subSet = [];    //Make sure we begin with a completely empty subset before continuing ...

        for (i=0; i<cnt; i++)

            subSet.push(baseSet[tmpIndices[i]]);    //Create the current subset, using items selected from the
                                                    //base set, using the indices array (which will change as we
                                                    //continue scanning) ...

    //Add the subset thus created to the result set ...

        result.push(subSet);

    //Now update the indices used to select the elements of the subset. At the start, idx will point to the
    //rightmost index in the indices array, but the moment that index moves out of bounds with respect to the
    //base set, attention will be shifted to the next left index.

        test = tmpIndices[idx] + 1;

        if (test >= bLen)
        {
        //Here, we're about to move out of bounds with respect to the base set. We therefore need to scan back,
        //and update indices to the left of the current one. Find the leftmost index in the indices array that
        //isn't going to  move out of bounds with respect to the base set ...

            tmpIdx = idx - 1;
            incr = 1;

            inBounds = false;       //Assume at start that the index we're checking in the loop below is out of bounds
            checkBounds = true;

            while (checkBounds)
            {
                if (tmpIdx < 0)
                {
                    checkBounds = false;    //Exit immediately at this point
                }
                else
                {
                    newIndex = tmpIndices[tmpIdx] + 1;
                    test = newIndex + incr;

                    if (test >= bLen)
                    {
                    //Here, incrementing the current selected index will take that index out of bounds, so
                    //we move on to the next index to the left ...

                        tmpIdx--;
                        incr++;
                    }
                    else
                    {
                    //Here, the index will remain in bounds if we increment it, so we
                    //exit the loop and signal that we're in bounds ...

                        inBounds = true;
                        checkBounds = false;

                    //End if/else
                    }

                //End if 
                }               
            //End while
            }
    //At this point, if we'er still in bounds, then we continue generating subsets, but if not, we abort immediately.

            if (!inBounds)
                done = true;
            else
            {
            //Here, we're still in bounds. We need to update the indices accordingly. NOTE: at this point, although a
            //left positioned index in the indices array may still be in bounds, incrementing it to generate indices to
            //the right may take those indices out of bounds. We therefore need to check this as we perform the index
            //updating of the indices array.

                tmpIndices[tmpIdx] = newIndex;

                inBounds = true;
                checking = true;
                i = tmpIdx + 1;

                while (checking)
                {
                    test = tmpIndices[i - 1] + 1;   //Find out if incrementing the left adjacent index takes it out of bounds

                    if (test >= bLen)
                    {
                        inBounds = false;           //If we move out of bounds, exit NOW ...
                        checking = false;
                    }
                    else
                    {
                        tmpIndices[i] = test;       //Otherwise, update the indices array ...

                        i++;                        //Now move on to the next index to the right in the indices array ...

                        checking = (i < cnt);       //And continue until we've exhausted all the indices array elements ...
                    //End if/else
                    }
                //End while
                }
                //At this point, if the above updating of the indices array has moved any of its elements out of bounds,
                //we abort subset construction from this point ...
                if (!inBounds)
                    done = true;
            //End if/else
            }
        }
        else
        {
        //Here, the rightmost index under consideration isn't moving out of bounds with respect to the base set when
        //we increment it, so we simply increment and continue the loop ...
            tmpIndices[idx] = test;
        //End if
        }
    //End while
    }
    return(result);
//End function
}


function MakePowerSet(baseSet)
{
    var bLen = baseSet.length;
    var result = [];
    var i = 0;
    var partialSet = [];

    result.push([]);    //add the empty set to the power set

    for (i=1; i<bLen; i++)
    {
        partialSet = MakeCombinationSubsets(baseSet, i);
        result = result.concat(partialSet);
    //End i loop
    }
    //Now, finally, add the base set itself to the power set to make it complete ...

    partialSet = [];
    partialSet.push(baseSet);
    result = result.concat(partialSet);

    return(result);
    //End function
}

我用集合["a"， "b"， "c"， "d"， "e"， "f"]作为基本集进行了测试，并运行代码以产生以下幂集:

[]
["a"]
["b"]
["c"]
["d"]
["e"]
["f"]
["a","b"]
["a","c"]
["a","d"]
["a","e"]
["a","f"]
["b","c"]
["b","d"]
["b","e"]
["b","f"]
["c","d"]
["c","e"]
["c","f"]
["d","e"]
["d","f"]
["e","f"]
["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"]
["a","b","c","d"]
["a","b","c","e"]
["a","b","c","f"]
["a","b","d","e"]
["a","b","d","f"]
["a","b","e","f"]
["a","c","d","e"]
["a","c","d","f"]
["a","c","e","f"]
["a","d","e","f"]
["b","c","d","e"]
["b","c","d","f"]
["b","c","e","f"]
["b","d","e","f"]
["c","d","e","f"]
["a","b","c","d","e"]
["a","b","c","d","f"]
["a","b","c","e","f"]
["a","b","d","e","f"]
["a","c","d","e","f"]
["b","c","d","e","f"]
["a","b","c","d","e","f"]

只要复制粘贴这两个函数“原样”，你就有了提取n元素集的不同k子集所需的基本知识，并生成该n元素集的幂集(如果你愿意的话)。

我并不是说这很优雅，只是说它在经过大量的测试(并在调试阶段将空气变为蓝色:)之后可以工作。

赶时髦，发布另一个解决方案。这是一个通用的Java实现。输入:(int k)是要选择的元素数量，(List<T> List)是要选择的列表。返回一个组合列表(list < list <T>>)。

public static <T> List<List<T>> getCombinations(int k, List<T> list) {
    List<List<T>> combinations = new ArrayList<List<T>>();
    if (k == 0) {
        combinations.add(new ArrayList<T>());
        return combinations;
    }
    for (int i = 0; i < list.size(); i++) {
        T element = list.get(i);
        List<T> rest = getSublist(list, i+1);
        for (List<T> previous : getCombinations(k-1, rest)) {
            previous.add(element);
            combinations.add(previous);
        }
    }
    return combinations;
}

public static <T> List<T> getSublist(List<T> list, int i) {
    List<T> sublist = new ArrayList<T>();
    for (int j = i; j < list.size(); j++) {
        sublist.add(list.get(j));
    }
    return sublist;
}