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。

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。

Haskell中的简单递归算法

import Data.List

combinations 0 lst = [[]]
combinations n lst = do
    (x:xs) <- tails lst
    rest   <- combinations (n-1) xs
    return $ x : rest

我们首先定义特殊情况，即选择零元素。它产生一个单一的结果，这是一个空列表(即一个包含空列表的列表)。

对于n> 0, x遍历列表中的每一个元素xs是x之后的每一个元素。

Rest通过对组合的递归调用从xs中选取n - 1个元素。该函数的最终结果是一个列表，其中每个元素都是x: rest(即对于x和rest的每个不同值，x为头部，rest为尾部的列表)。

> combinations 3 "abcde"
["abc","abd","abe","acd","ace","ade","bcd","bce","bde","cde"]

当然，由于Haskell是懒惰的，列表是根据需要逐渐生成的，因此您可以部分计算指数级的大组合。

> let c = combinations 8 "abcdefghijklmnopqrstuvwxyz"
> take 10 c
["abcdefgh","abcdefgi","abcdefgj","abcdefgk","abcdefgl","abcdefgm","abcdefgn",
 "abcdefgo","abcdefgp","abcdefgq"]

下面是我最近用Java写的一段代码，它计算并返回从“outOf”元素中“num”元素的所有组合。

// author: Sourabh Bhat (heySourabh@gmail.com)

public class Testing
{
    public static void main(String[] args)
    {

// Test case num = 5, outOf = 8.

        int num = 5;
        int outOf = 8;
        int[][] combinations = getCombinations(num, outOf);
        for (int i = 0; i < combinations.length; i++)
        {
            for (int j = 0; j < combinations[i].length; j++)
            {
                System.out.print(combinations[i][j] + " ");
            }
            System.out.println();
        }
    }

    private static int[][] getCombinations(int num, int outOf)
    {
        int possibilities = get_nCr(outOf, num);
        int[][] combinations = new int[possibilities][num];
        int arrayPointer = 0;

        int[] counter = new int[num];

        for (int i = 0; i < num; i++)
        {
            counter[i] = i;
        }
        breakLoop: while (true)
        {
            // Initializing part
            for (int i = 1; i < num; i++)
            {
                if (counter[i] >= outOf - (num - 1 - i))
                    counter[i] = counter[i - 1] + 1;
            }

            // Testing part
            for (int i = 0; i < num; i++)
            {
                if (counter[i] < outOf)
                {
                    continue;
                } else
                {
                    break breakLoop;
                }
            }

            // Innermost part
            combinations[arrayPointer] = counter.clone();
            arrayPointer++;

            // Incrementing part
            counter[num - 1]++;
            for (int i = num - 1; i >= 1; i--)
            {
                if (counter[i] >= outOf - (num - 1 - i))
                    counter[i - 1]++;
            }
        }

        return combinations;
    }

    private static int get_nCr(int n, int r)
    {
        if(r > n)
        {
            throw new ArithmeticException("r is greater then n");
        }
        long numerator = 1;
        long denominator = 1;
        for (int i = n; i >= r + 1; i--)
        {
            numerator *= i;
        }
        for (int i = 2; i <= n - r; i++)
        {
            denominator *= i;
        }

        return (int) (numerator / denominator);
    }
}

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

我在c++中为组合创建了一个通用类。 它是这样使用的。

char ar[] = "0ABCDEFGH";
nCr ncr(8, 3);
while(ncr.next()) {
    for(int i=0; i<ncr.size(); i++) cout << ar[ncr[i]];
    cout << ' ';
}

我的库ncr[i]从1返回，而不是从0返回。 这就是为什么数组中有0。 如果你想考虑订单，只需将nCr class改为nPr即可。 用法是相同的。

结果

美国广播公司 ABD 安倍 沛富 ABG ABH 澳洲牧牛犬 王牌 ACF ACG 呵呀 正面 ADF ADG 抗利尿激素 时 AEG AEH 二自由度陀螺仪 AFH 啊 BCD 公元前 供应量 波士顿咨询公司 BCH 12 快速公车提供 BDG BDH 性能试验 求 本· 高炉煤气 BFH 使用BGH CDE 提供 CDG 鼎晖 欧共体语言教学大纲的 CEG 另一 CFG CFH 全息 DEF 度 电气设施 脱硫 干扰 DGH EFG EFH EGH FGH

下面是头文件。

#pragma once
#include <exception>

class NRexception : public std::exception
{
public:
    virtual const char* what() const throw() {
        return "Combination : N, R should be positive integer!!";
    }
};

class Combination
{
public:
    Combination(int n, int r);
    virtual ~Combination() { delete [] ar;}
    int& operator[](unsigned i) {return ar[i];}
    bool next();
    int size() {return r;}
    static int factorial(int n);

protected:
    int* ar;
    int n, r;
};

class nCr : public Combination
{
public: 
    nCr(int n, int r);
    bool next();
    int count() const;
};

class nTr : public Combination
{
public:
    nTr(int n, int r);
    bool next();
    int count() const;
};

class nHr : public nTr
{
public:
    nHr(int n, int r) : nTr(n,r) {}
    bool next();
    int count() const;
};

class nPr : public Combination
{
public:
    nPr(int n, int r);
    virtual ~nPr() {delete [] on;}
    bool next();
    void rewind();
    int count() const;

private:
    bool* on;
    void inc_ar(int i);
};

以及执行。

#include "combi.h"
#include <set>
#include<cmath>

Combination::Combination(int n, int r)
{
    //if(n < 1 || r < 1) throw NRexception();
    ar = new int[r];
    this->n = n;
    this->r = r;
}

int Combination::factorial(int n) 
{
    return n == 1 ? n : n * factorial(n-1);
}

int nPr::count() const
{
    return factorial(n)/factorial(n-r);
}

int nCr::count() const
{
    return factorial(n)/factorial(n-r)/factorial(r);
}

int nTr::count() const
{
    return pow(n, r);
}

int nHr::count() const
{
    return factorial(n+r-1)/factorial(n-1)/factorial(r);
}

nCr::nCr(int n, int r) : Combination(n, r)
{
    if(r == 0) return;
    for(int i=0; i<r-1; i++) ar[i] = i + 1;
    ar[r-1] = r-1;
}

nTr::nTr(int n, int r) : Combination(n, r)
{
    for(int i=0; i<r-1; i++) ar[i] = 1;
    ar[r-1] = 0;
}

bool nCr::next()
{
    if(r == 0) return false;
    ar[r-1]++;
    int i = r-1;
    while(ar[i] == n-r+2+i) {
        if(--i == -1) return false;
        ar[i]++;
    }
    while(i < r-1) ar[i+1] = ar[i++] + 1;
    return true;
}

bool nTr::next()
{
    ar[r-1]++;
    int i = r-1;
    while(ar[i] == n+1) {
        ar[i] = 1;
        if(--i == -1) return false;
        ar[i]++;
    }
    return true;
}

bool nHr::next()
{
    ar[r-1]++;
    int i = r-1;
    while(ar[i] == n+1) {
        if(--i == -1) return false;
        ar[i]++;
    }
    while(i < r-1) ar[i+1] = ar[i++];
    return true;
}

nPr::nPr(int n, int r) : Combination(n, r)
{
    on = new bool[n+2];
    for(int i=0; i<n+2; i++) on[i] = false;
    for(int i=0; i<r; i++) {
        ar[i] = i + 1;
        on[i] = true;
    }
    ar[r-1] = 0;
}

void nPr::rewind()
{
    for(int i=0; i<r; i++) {
        ar[i] = i + 1;
        on[i] = true;
    }
    ar[r-1] = 0;
}

bool nPr::next()
{   
    inc_ar(r-1);

    int i = r-1;
    while(ar[i] == n+1) {
        if(--i == -1) return false;
        inc_ar(i);
    }
    while(i < r-1) {
        ar[++i] = 0;
        inc_ar(i);
    }
    return true;
}

void nPr::inc_ar(int i)
{
    on[ar[i]] = false;
    while(on[++ar[i]]);
    if(ar[i] != n+1) on[ar[i]] = true;
}