《计算机编程艺术，卷4A:组合算法，第1部分》第7.2.1.3节中算法L(字典组合)的C代码:

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

void visit(int* c, int t) 
{
  // for (int j = 1; j <= t; j++)
  for (int j = t; j > 0; j--)
    printf("%d ", c[j]);
  printf("\n");
}

int* initialize(int n, int t) 
{
  // c[0] not used
  int *c = (int*) malloc((t + 3) * sizeof(int));

  for (int j = 1; j <= t; j++)
    c[j] = j - 1;
  c[t+1] = n;
  c[t+2] = 0;
  return c;
}

void comb(int n, int t) 
{
  int *c = initialize(n, t);
  int j;

  for (;;) {
    visit(c, t);
    j = 1;
    while (c[j]+1 == c[j+1]) {
      c[j] = j - 1;
      ++j;
    }
    if (j > t) 
      return;
    ++c[j];
  }
  free(c);
}

int main(int argc, char *argv[])
{
  comb(5, 3);
  return 0;
}

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。

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;
}

《计算机程序设计艺术》第4卷第3册有大量这样的内容，它们可能比我描述的更适合你的特定情况。

格雷码

你会遇到的一个问题当然是内存，很快，你会在你的集合中遇到20个元素的问题——20C3 = 1140。如果你想遍历这个集合，最好使用修改过的灰码算法，这样你就不会把它们都保存在内存中。这将从前一个组合中生成下一个组合并避免重复。有很多不同的用途。我们想要最大化连续组合之间的差异吗?最小化?等等。

一些描述灰色代码的原始论文:

Hamilton路径与最小变化算法 相邻交换组合生成算法

以下是涉及该主题的其他一些论文:

Eades、Hickey、Read相邻交换组合生成算法的高效实现(PDF, Pascal代码) 结合发电机 组合灰色编码综述(PostScript) 灰色编码的一种算法

Chase's Twiddle(算法)

菲利普·J·蔡斯，《算法382:N个对象中M个对象的组合》(1970)

该算法在C…

按字典顺序排列的组合索引(Buckles算法515)

还可以通过索引(按字典顺序)引用组合。意识到索引应该是基于索引从右到左的一些变化，我们可以构造一些应该恢复组合的东西。

So, we have a set {1,2,3,4,5,6}... and we want three elements. Let's say {1,2,3} we can say that the difference between the elements is one and in order and minimal. {1,2,4} has one change and is lexicographically number 2. So the number of 'changes' in the last place accounts for one change in the lexicographical ordering. The second place, with one change {1,3,4} has one change but accounts for more change since it's in the second place (proportional to the number of elements in the original set).

我所描述的方法是一种解构，从集合到索引，我们需要做相反的事情——这要复杂得多。这就是巴克尔斯解决问题的方法。我写了一些C来计算它们，做了一些小改动——我使用集合的索引而不是一个数字范围来表示集合，所以我们总是从0…n开始工作。 注意:

由于组合是无序的，{1,3,2}={1,2,3}——我们将它们按字典顺序排列。 该方法有一个隐式的0来开始第一个差值集。

词典顺序组合索引(麦卡弗里)

还有另一种方法:，它的概念更容易掌握和编程，但它没有Buckles的优化。幸运的是，它也不会产生重复的组合:

最大化的集合，其中。

例如:27 = C (6, 4) + C (5,3) + C (2, 2) + C(1, 1)。那么，第27个单词的字典组合是{1,2,5,6}，它们是你想要查找的任何集合的索引。下面的例子(OCaml)，需要选择函数，留给读者:

(* this will find the [x] combination of a [set] list when taking [k] elements *)
let combination_maccaffery set k x =
    (* maximize function -- maximize a that is aCb              *)
    (* return largest c where c < i and choose(c,i) <= z        *)
    let rec maximize a b x =
        if (choose a b ) <= x then a else maximize (a-1) b x
    in
    let rec iterate n x i = match i with
        | 0 -> []
        | i ->
            let max = maximize n i x in
            max :: iterate n (x - (choose max i)) (i-1)
    in
    if x < 0 then failwith "errors" else
    let idxs =  iterate (List.length set) x k in
    List.map (List.nth set) (List.sort (-) idxs)

一个小而简单的组合迭代器

为了教学目的，提供了以下两个算法。它们实现了一个迭代器和(更通用的)文件夹整体组合。 它们尽可能快，复杂度为O(nCk)。内存消耗受k约束。

我们将从迭代器开始，它将为每个组合调用用户提供的函数

let iter_combs n k f =
  let rec iter v s j =
    if j = k then f v
    else for i = s to n - 1 do iter (i::v) (i+1) (j+1) done in
  iter [] 0 0

更通用的版本将从初始状态开始调用用户提供的函数和状态变量。因为我们需要在不同的状态之间传递状态，所以我们不使用for循环，而是使用递归，

let fold_combs n k f x =
  let rec loop i s c x =
    if i < n then
      loop (i+1) s c @@
      let c = i::c and s = s + 1 and i = i + 1 in
      if s < k then loop i s c x else f c x
    else x in
  loop 0 0 [] x

最近在IronScripter网站上有一个PowerShell挑战，需要一个n- choice -k的解决方案。我在那里发布了一个解决方案，但这里有一个更通用的版本。

AllK开关用于控制输出是长度为ChooseK的组合，还是长度为1到ChooseK的组合。 Prefix参数实际上是输出字符串的累加器，但其效果是为初始调用传递的值实际上会为每一行输出添加前缀。

function Get-NChooseK
{

    [CmdletBinding()]

    Param
    (

        [String[]]
        $ArrayN

    ,   [Int]
        $ChooseK

    ,   [Switch]
        $AllK

    ,   [String]
        $Prefix = ''

    )

    PROCESS
    {
        # Validate the inputs
        $ArrayN = $ArrayN | Sort-Object -Unique

        If ($ChooseK -gt $ArrayN.Length)
        {
            Write-Error "Can't choose $ChooseK items when only $($ArrayN.Length) are available." -ErrorAction Stop
        }

        # Control the output
        $firstK = If ($AllK) { 1 } Else { $ChooseK }

        # Get combinations
        $firstK..$ChooseK | ForEach-Object {

            $thisK = $_

            $ArrayN[0..($ArrayN.Length-($thisK--))] | ForEach-Object {
                If ($thisK -eq 0)
                {
                    Write-Output ($Prefix+$_)
                }
                Else
                {
                    Get-NChooseK -Array ($ArrayN[($ArrayN.IndexOf($_)+1)..($ArrayN.Length-1)]) -Choose $thisK -AllK:$false -Prefix ($Prefix+$_)
                }
            }

        }
    }

}

例如:

PS C:\>$ArrayN  = 'E','B','C','A','D'
PS C:\>$ChooseK = 3
PS C:\>Get-NChooseK -ArrayN $ArrayN -ChooseK $ChooseK
ABC
ABD
ABE
ACD
ACE
ADE
BCD
BCE
BDE
CDE

这是我用c++写的命题

我尽可能少地限制迭代器类型，所以这个解决方案假设只有前向迭代器，它可以是const_iterator。这应该适用于任何标准容器。在参数没有意义的情况下，它抛出std:: invalid_argument

#include <vector>
#include <stdexcept>

template <typename Fci> // Fci - forward const iterator
std::vector<std::vector<Fci> >
enumerate_combinations(Fci begin, Fci end, unsigned int combination_size)
{
    if(begin == end && combination_size > 0u)
        throw std::invalid_argument("empty set and positive combination size!");
    std::vector<std::vector<Fci> > result; // empty set of combinations
    if(combination_size == 0u) return result; // there is exactly one combination of
                                              // size 0 - emty set
    std::vector<Fci> current_combination;
    current_combination.reserve(combination_size + 1u); // I reserve one aditional slot
                                                        // in my vector to store
                                                        // the end sentinel there.
                                                        // The code is cleaner thanks to that
    for(unsigned int i = 0u; i < combination_size && begin != end; ++i, ++begin)
    {
        current_combination.push_back(begin); // Construction of the first combination
    }
    // Since I assume the itarators support only incrementing, I have to iterate over
    // the set to get its size, which is expensive. Here I had to itrate anyway to  
    // produce the first cobination, so I use the loop to also check the size.
    if(current_combination.size() < combination_size)
        throw std::invalid_argument("combination size > set size!");
    result.push_back(current_combination); // Store the first combination in the results set
    current_combination.push_back(end); // Here I add mentioned earlier sentinel to
                                        // simplyfy rest of the code. If I did it 
                                        // earlier, previous statement would get ugly.
    while(true)
    {
        unsigned int i = combination_size;
        Fci tmp;                            // Thanks to the sentinel I can find first
        do                                  // iterator to change, simply by scaning
        {                                   // from right to left and looking for the
            tmp = current_combination[--i]; // first "bubble". The fact, that it's 
            ++tmp;                          // a forward iterator makes it ugly but I
        }                                   // can't help it.
        while(i > 0u && tmp == current_combination[i + 1u]);

        // Here is probably my most obfuscated expression.
        // Loop above looks for a "bubble". If there is no "bubble", that means, that
        // current_combination is the last combination, Expression in the if statement
        // below evaluates to true and the function exits returning result.
        // If the "bubble" is found however, the ststement below has a sideeffect of 
        // incrementing the first iterator to the left of the "bubble".
        if(++current_combination[i] == current_combination[i + 1u])
            return result;
        // Rest of the code sets posiotons of the rest of the iterstors
        // (if there are any), that are to the right of the incremented one,
        // to form next combination

        while(++i < combination_size)
        {
            current_combination[i] = current_combination[i - 1u];
            ++current_combination[i];
        }
        // Below is the ugly side of using the sentinel. Well it had to haave some 
        // disadvantage. Try without it.
        result.push_back(std::vector<Fci>(current_combination.begin(),
                                          current_combination.end() - 1));
    }
}