寻找所有可能的数字组合以达到给定的总和


232

您将如何测试一组给定N数字的加法的所有可能组合,以便将它们累加到给定的最终数字?

一个简单的例子:

  • 要添加的一组数字: N = {1,5,22,15,0,...}
  • 所需结果: 12345

@James-我认为您的问题需要澄清。都有些什么样的规矩?你能挑任何数字吗?集合中有什么数字?你有什么限制?
jmort253'1

9
维基百科文章(en.wikipedia.org/wiki/Subset_sum_problem)甚至提到此问题是NP完全问题类别的很好的介绍。
user57368 2011年

1
@ jmort253:我认为除了拥有一组正整数且小于目标整数的整数之外,没有其他限制。可以使用任何数字组合。这不是家庭作业,而是如果您申请一些工作将给您解决的问题。我通常可以在需要时考虑一个算法,但是我不确定如何查看这样的内容。它需要以某种方式分解(递归?)。
James P.

3
@James,您需要组合的总和还是子集的总和?
st0le 2011年

6
我们可以多次使用原始集合的相同元素吗?例如,如果输入为{1,2,3,5}并且目标为10,则5 + 5 = 10是否可以接受?
alampada

Answers:


248

可以通过递归组合所有可能的总和来过滤掉达到目标的总和,从而解决此问题。这是Python中的算法:

def subset_sum(numbers, target, partial=[]):
    s = sum(partial)

    # check if the partial sum is equals to target
    if s == target: 
        print "sum(%s)=%s" % (partial, target)
    if s >= target:
        return  # if we reach the number why bother to continue

    for i in range(len(numbers)):
        n = numbers[i]
        remaining = numbers[i+1:]
        subset_sum(remaining, target, partial + [n]) 


if __name__ == "__main__":
    subset_sum([3,9,8,4,5,7,10],15)

    #Outputs:
    #sum([3, 8, 4])=15
    #sum([3, 5, 7])=15
    #sum([8, 7])=15
    #sum([5, 10])=15

在以下Standford的Abstract Programming演讲中,很好地解释了这种算法-该视频非常可取,以了解递归如何工作以生成解的置换。

编辑

上面作为生成器函数,使其更加有用。由于,需要Python 3.3+ yield from

def subset_sum(numbers, target, partial=[], partial_sum=0):
    if partial_sum == target:
        yield partial
    if partial_sum >= target:
        return
    for i, n in enumerate(numbers):
        remaining = numbers[i + 1:]
        yield from subset_sum(remaining, target, partial + [n], partial_sum + n)

这是相同算法的Java版本:

package tmp;

import java.util.ArrayList;
import java.util.Arrays;

class SumSet {
    static void sum_up_recursive(ArrayList<Integer> numbers, int target, ArrayList<Integer> partial) {
       int s = 0;
       for (int x: partial) s += x;
       if (s == target)
            System.out.println("sum("+Arrays.toString(partial.toArray())+")="+target);
       if (s >= target)
            return;
       for(int i=0;i<numbers.size();i++) {
             ArrayList<Integer> remaining = new ArrayList<Integer>();
             int n = numbers.get(i);
             for (int j=i+1; j<numbers.size();j++) remaining.add(numbers.get(j));
             ArrayList<Integer> partial_rec = new ArrayList<Integer>(partial);
             partial_rec.add(n);
             sum_up_recursive(remaining,target,partial_rec);
       }
    }
    static void sum_up(ArrayList<Integer> numbers, int target) {
        sum_up_recursive(numbers,target,new ArrayList<Integer>());
    }
    public static void main(String args[]) {
        Integer[] numbers = {3,9,8,4,5,7,10};
        int target = 15;
        sum_up(new ArrayList<Integer>(Arrays.asList(numbers)),target);
    }
}

这是完全相同的启发式方法。我的Java有点生锈,但我认为它很容易理解。

Java解决方案的C#转换:( 通过@JeremyThompson)

public static void Main(string[] args)
{
    List<int> numbers = new List<int>() { 3, 9, 8, 4, 5, 7, 10 };
    int target = 15;
    sum_up(numbers, target);
}

private static void sum_up(List<int> numbers, int target)
{
    sum_up_recursive(numbers, target, new List<int>());
}

private static void sum_up_recursive(List<int> numbers, int target, List<int> partial)
{
    int s = 0;
    foreach (int x in partial) s += x;

    if (s == target)
        Console.WriteLine("sum(" + string.Join(",", partial.ToArray()) + ")=" + target);

    if (s >= target)
        return;

    for (int i = 0; i < numbers.Count; i++)
    {
        List<int> remaining = new List<int>();
        int n = numbers[i];
        for (int j = i + 1; j < numbers.Count; j++) remaining.Add(numbers[j]);

        List<int> partial_rec = new List<int>(partial);
        partial_rec.Add(n);
        sum_up_recursive(remaining, target, partial_rec);
    }
}

Ruby解决方案: (@ emaillenin提供)

def subset_sum(numbers, target, partial=[])
  s = partial.inject 0, :+
# check if the partial sum is equals to target

  puts "sum(#{partial})=#{target}" if s == target

  return if s >= target # if we reach the number why bother to continue

  (0..(numbers.length - 1)).each do |i|
    n = numbers[i]
    remaining = numbers.drop(i+1)
    subset_sum(remaining, target, partial + [n])
  end
end

subset_sum([3,9,8,4,5,7,10],15)

编辑:复杂性讨论

正如其他人所提到的,这是一个NP难题。可以在指数时间O(2 ^ n)中求解,例如对于n = 10,将有1024个可能的解。如果您要达到的目标范围较小,则此算法有效。因此,例如:

subset_sum([1,2,3,4,5,6,7,8,9,10],100000) 生成1024个分支,因为目标从不滤除可能的解决方案。

另一方面,subset_sum([1,2,3,4,5,6,7,8,9,10],10)仅生成175个分支,因为要达到的目标10必须过滤掉许多组合。

如果NTarget大,则应进入解决方案的近似版本。


1
Java优化:ArrayList <Integer> partial_rec = new ArrayList <Integer>(partial); partial_rec.add(n); 这会做部分副本。并因此加上O(N)。更好的方法是只对“ partial.add(n)”进行递归,然后“ partial.remove(partial.size -1)。我重新运行您的代码以确保。它工作正常
Christian Bongiorno,2015年

4
此解决方案不适用于所有情况。考虑[1, 2, 0, 6, -3, 3], 3-它仅[1,2], [0,3], [3]在缺少情况时输出,例如[6, -3, 3]
LiraNuna

11
它也没有为每个组合的工作,例如[1, 2, 5], 5仅输出[5]的时候[1, 1, 1, 1, 1][2, 2, 1][2, 1, 1, 1]有解决方案。
cbrad

3
@cbrad那是因为i+1in remaining = numbers[i+1:]。看来该算法不允许重复。
列昂尼德·瓦西列夫

1
@cbrad为了得到还解决方案,包括重复喜欢[1, 1, 3]看看stackoverflow.com/a/34971783/3684296(蟒蛇)
梅萨

36

这个问题的解决方案已经在Internet上被提供了100万次。这个问题叫做硬币兑换问题。可以在http://rosettacode.org/wiki/Count_the_coins上找到解决方案,并在http://jaqm.ro/issues/volume-5,issue-2/pdfs/patterson_harmel.pdf上找到它的数学模型(或通过Google 找零)问题)。

顺便说一下,Tsagadai的Scala解决方案很有趣。此示例产生1或0。作为副作用,它在控制台上列出了所有可能的解决方案。它显示了解决方案,但是无法使其以任何方式使用。

为了尽可能有用,代码应返回a List[List[Int]],以允许获得解决方案的数量(列表列表的长度),“最佳”解决方案(最短列表)或所有可能的解决方案。

这是一个例子。它效率很低,但是很容易理解。

object Sum extends App {

  def sumCombinations(total: Int, numbers: List[Int]): List[List[Int]] = {

    def add(x: (Int, List[List[Int]]), y: (Int, List[List[Int]])): (Int, List[List[Int]]) = {
      (x._1 + y._1, x._2 ::: y._2)
    }

    def sumCombinations(resultAcc: List[List[Int]], sumAcc: List[Int], total: Int, numbers: List[Int]): (Int, List[List[Int]]) = {
      if (numbers.isEmpty || total < 0) {
        (0, resultAcc)
      } else if (total == 0) {
        (1, sumAcc :: resultAcc)
      } else {
        add(sumCombinations(resultAcc, sumAcc, total, numbers.tail), sumCombinations(resultAcc, numbers.head :: sumAcc, total - numbers.head, numbers))
      }
    }

    sumCombinations(Nil, Nil, total, numbers.sortWith(_ > _))._2
  }

  println(sumCombinations(15, List(1, 2, 5, 10)) mkString "\n")
}

运行时,它显示:

List(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1)
List(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2)
List(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2)
List(1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2)
List(1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2)
List(1, 1, 1, 1, 1, 2, 2, 2, 2, 2)
List(1, 1, 1, 2, 2, 2, 2, 2, 2)
List(1, 2, 2, 2, 2, 2, 2, 2)
List(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 5)
List(1, 1, 1, 1, 1, 1, 1, 1, 2, 5)
List(1, 1, 1, 1, 1, 1, 2, 2, 5)
List(1, 1, 1, 1, 2, 2, 2, 5)
List(1, 1, 2, 2, 2, 2, 5)
List(2, 2, 2, 2, 2, 5)
List(1, 1, 1, 1, 1, 5, 5)
List(1, 1, 1, 2, 5, 5)
List(1, 2, 2, 5, 5)
List(5, 5, 5)
List(1, 1, 1, 1, 1, 10)
List(1, 1, 1, 2, 10)
List(1, 2, 2, 10)
List(5, 10)

sumCombinations()函数可以单独使用,并且可以进一步分析结果以显示“最佳”解决方案(最短列表)或解决方案数量(列表数量)。

请注意,即使这样,也可能无法完全满足要求。解决方案中每个列表的顺序可能很重要。在这种情况下,每个列表的重复时间必须与元素的组合相同。或者,我们可能只对不同的组合感兴趣。

例如,我们可能认为List(5, 10)应该给出两个组合:List(5, 10)List(10, 5)。对于List(5, 5, 5)它可能给三个结合或只有一个,根据需求。对于整数,这三个排列是等效的,但是如果我们要处理硬币,例如“硬币更换问题”,则不是。

要求中也没有说明每个数字(或硬币)只能使用一次还是多次的问题。我们可以(并且应该!)将问题概括为每个数字出现的列表。在现实生活中,这转化为“用一组硬币(而不是一组硬币值)赚取一定数量的钱的可能方法是什么”。最初的问题只是这种情况的一个特例,在这种情况下,我们需要根据每个硬币的出现次数来使每个硬币的价值合计。


14
这个问题与硬币找零问题并不完全相同。OP要求所有的组合,而不仅仅是最小的组合。并且,假定集合中的整数可以为负数。因此,对于该硬币硬币问题的某些优化是不可能的。
ThomasMcLeod

5
而且这个问题也允许重复项目,我不确定OP是否希望这样做,但更多是背包问题
caub 2014年

34

Haskell中

filter ((==) 12345 . sum) $ subsequences [1,5,22,15,0,..]

J

(]#~12345=+/@>)(]<@#~[:#:@i.2^#)1 5 22 15 0 ...

您可能会注意到,两者都采用相同的方法,并将问题分为两部分:生成功率集的每个成员,并将每个成员的总和检查到目标。

还有其他解决方案,但这是最直接的。

您是否需要帮助,或者需要其他方法?


3
哇,那是一些非常简洁的代码。我对你的回答很好。我想我一般只需要阅读一些算法。当您激发了我的好奇心时,我将看看这两种语言的语法。
James P.

我刚刚安装了Haskell进行了尝试,绝对不能仅仅将其粘贴并执行它,还有not in scope: 'subsequences'指针吗?
哈特CO

4
@HartCO派对晚了一点,但是import Data.List
Jir

28

JavaScript版本:

function subsetSum(numbers, target, partial) {
  var s, n, remaining;

  partial = partial || [];

  // sum partial
  s = partial.reduce(function (a, b) {
    return a + b;
  }, 0);

  // check if the partial sum is equals to target
  if (s === target) {
    console.log("%s=%s", partial.join("+"), target)
  }

  if (s >= target) {
    return;  // if we reach the number why bother to continue
  }

  for (var i = 0; i < numbers.length; i++) {
    n = numbers[i];
    remaining = numbers.slice(i + 1);
    subsetSum(remaining, target, partial.concat([n]));
  }
}

subsetSum([3,9,8,4,5,7,10],15);

// output:
// 3+8+4=15
// 3+5+7=15
// 8+7=15
// 5+10=15


该代码已在片错误,应remaining = numbers.slice(); remaining.slice(i + 1);以其他方式numbers.slice(i + 1);改变了数字阵列
Emeeus

@Emeeus,我认为那不是真的。slice返回(浅)副本,但不修改numbers数组。
达里奥·塞德尔

@DarioSeidl是的,slice返回一个副本,它不修改数组,这就是要点,这就是为什么如果不将其分配给变量,则不会对其进行更改。在这种情况下,据我了解,我们必须通过修改后的版本,而不是原始版本。看到这个jsfiddle.net/che06t3w/1
Emeeus

1
@Redu ...例如,一个简单的方法是,我们可以稍微修改算法并使用内部函数:jsbin.com/lecokaw/edit?js,console
rbarilani

1
给定的代码不一定会得到所有组合。例如,放置[1,2],3仅返回1 + 2 = 3而不是1 + 1 + 1或2 + 1
JuicY_Burrito

12

相同算法的C ++版本

#include <iostream>
#include <list>
void subset_sum_recursive(std::list<int> numbers, int target, std::list<int> partial)
{
        int s = 0;
        for (std::list<int>::const_iterator cit = partial.begin(); cit != partial.end(); cit++)
        {
            s += *cit;
        }
        if(s == target)
        {
                std::cout << "sum([";

                for (std::list<int>::const_iterator cit = partial.begin(); cit != partial.end(); cit++)
                {
                    std::cout << *cit << ",";
                }
                std::cout << "])=" << target << std::endl;
        }
        if(s >= target)
            return;
        int n;
        for (std::list<int>::const_iterator ai = numbers.begin(); ai != numbers.end(); ai++)
        {
            n = *ai;
            std::list<int> remaining;
            for(std::list<int>::const_iterator aj = ai; aj != numbers.end(); aj++)
            {
                if(aj == ai)continue;
                remaining.push_back(*aj);
            }
            std::list<int> partial_rec=partial;
            partial_rec.push_back(n);
            subset_sum_recursive(remaining,target,partial_rec);

        }
}

void subset_sum(std::list<int> numbers,int target)
{
    subset_sum_recursive(numbers,target,std::list<int>());
}
int main()
{
    std::list<int> a;
    a.push_back (3); a.push_back (9); a.push_back (8);
    a.push_back (4);
    a.push_back (5);
    a.push_back (7);
    a.push_back (10);
    int n = 15;
    //std::cin >> n;
    subset_sum(a, n);
    return 0;
}

11

@msalvadores的C#版本代码答案

void Main()
{
    int[] numbers = {3,9,8,4,5,7,10};
    int target = 15;
    sum_up(new List<int>(numbers.ToList()),target);
}

static void sum_up_recursive(List<int> numbers, int target, List<int> part)
{
   int s = 0;
   foreach (int x in part)
   {
       s += x;
   }
   if (s == target)
   {
        Console.WriteLine("sum(" + string.Join(",", part.Select(n => n.ToString()).ToArray()) + ")=" + target);
   }
   if (s >= target)
   {
        return;
   }
   for (int i = 0;i < numbers.Count;i++)
   {
         var remaining = new List<int>();
         int n = numbers[i];
         for (int j = i + 1; j < numbers.Count;j++)
         {
             remaining.Add(numbers[j]);
         }
         var part_rec = new List<int>(part);
         part_rec.Add(n);
         sum_up_recursive(remaining,target,part_rec);
   }
}
static void sum_up(List<int> numbers, int target)
{
    sum_up_recursive(numbers,target,new List<int>());
}

4

我以为我会用这个问题的答案,但我没有,所以这是我的答案。它使用的是《计算机程序的结构和解释》中答案的修改版本。我认为这是一个更好的递归解决方案,应该让纯粹主义者更加满意。

我的答案是在Scala中(如果我的Scala很烂,我很抱歉,我才刚刚开始学习它)。该findSumCombinations疯狂是排序和独特的原始列表的递归以防止易受骗的人。

def findSumCombinations(target: Int, numbers: List[Int]): Int = {
  cc(target, numbers.distinct.sortWith(_ < _), List())
}

def cc(target: Int, numbers: List[Int], solution: List[Int]): Int = {
  if (target == 0) {println(solution); 1 }
  else if (target < 0 || numbers.length == 0) 0
  else 
    cc(target, numbers.tail, solution) 
    + cc(target - numbers.head, numbers, numbers.head :: solution)
}

要使用它:

 > findSumCombinations(12345, List(1,5,22,15,0,..))
 * Prints a whole heap of lists that will sum to the target *

4
Thank you.. ephemient

我已经将以上逻辑从python转换为php ..

<?php
$data = array(array(2,3,5,10,15),array(4,6,23,15,12),array(23,34,12,1,5));
$maxsum = 25;

print_r(bestsum($data,$maxsum));  //function call

function bestsum($data,$maxsum)
{
$res = array_fill(0, $maxsum + 1, '0');
$res[0] = array();              //base case
foreach($data as $group)
{
 $new_res = $res;               //copy res

  foreach($group as $ele)
  {
    for($i=0;$i<($maxsum-$ele+1);$i++)
    {   
        if($res[$i] != 0)
        {
            $ele_index = $i+$ele;
            $new_res[$ele_index] = $res[$i];
            $new_res[$ele_index][] = $ele;
        }
    }
  }

  $res = $new_res;
}

 for($i=$maxsum;$i>0;$i--)
  {
    if($res[$i]!=0)
    {
        return $res[$i];
        break;
    }
  }
return array();
}
?>

4

另一个python解决方案是使用itertools.combinations模块,如下所示:

#!/usr/local/bin/python

from itertools import combinations

def find_sum_in_list(numbers, target):
    results = []
    for x in range(len(numbers)):
        results.extend(
            [   
                combo for combo in combinations(numbers ,x)  
                    if sum(combo) == target
            ]   
        )   

    print results

if __name__ == "__main__":
    find_sum_in_list([3,9,8,4,5,7,10], 15)

输出: [(8, 7), (5, 10), (3, 8, 4), (3, 5, 7)]


它不起作用,例如:find_sum_in_list(range(0,8),4)。找到:[(4,),(0,4),(1,3),(0,1,3)]。但是(2,2)也是一个选择!
安德烈·阿劳霍

@AndreAraujo:使用0毫无意义,但是如果使用(1,8),则itertools.combinations_with_replacement可以工作,并且也输出2,2。
Rubenisme

@Rubenisme是的,伙计!问题是更换!谢谢!;-)
Andre Araujo,

4

这是R中的解决方案

subset_sum = function(numbers,target,partial=0){
  if(any(is.na(partial))) return()
  s = sum(partial)
  if(s == target) print(sprintf("sum(%s)=%s",paste(partial[-1],collapse="+"),target))
  if(s > target) return()
  for( i in seq_along(numbers)){
    n = numbers[i]
    remaining = numbers[(i+1):length(numbers)]
    subset_sum(remaining,target,c(partial,n))
  }
}

我正在寻找R中的解决方案,但该解决方案对我不起作用。例如,subset_sum(numbers = c(1:2), target = 5)return "sum(1+2+2)=5"。但是缺少组合1 + 1 + 1 + 1 + 1。将目标设置为更高的数字(例如20)会丢失更多的组合。
Frederick

您所描述的不是函数要返回的内容。查看接受的答案。2被重复两次的事实是R如何生成和子集序列的假象,而不是预期的行为。
马克

subset_sum(1:2, 4)应该不返回任何解决方案,因为没有加1和2的组合加到4。如果函数i的长度大于numbers
Mark

3

当复杂度O(t*N)(动态解决方案)大于指数算法时,这是一个非常适合小N和非常大的目标和的Java版本。我的版本在中间攻击中使用见面,同时进行了一些调整,以降低从经典天真O(n*2^n)到的复杂性O(2^(n/2))

如果要将其用于包含32至64个元素的集合,则应将int代表步进功能中当前子集的更改为,long尽管随着集合大小的增加,性能显然会急剧下降。如果要将其用于元素数量为奇数的集合,则应在集合中添加0以使其为偶数。

import java.util.ArrayList;
import java.util.List;

public class SubsetSumMiddleAttack {
    static final int target = 100000000;
    static final int[] set = new int[]{ ... };

    static List<Subset> evens = new ArrayList<>();
    static List<Subset> odds = new ArrayList<>();

    static int[][] split(int[] superSet) {
        int[][] ret = new int[2][superSet.length / 2]; 

        for (int i = 0; i < superSet.length; i++) ret[i % 2][i / 2] = superSet[i];

        return ret;
    }

    static void step(int[] superSet, List<Subset> accumulator, int subset, int sum, int counter) {
        accumulator.add(new Subset(subset, sum));
        if (counter != superSet.length) {
            step(superSet, accumulator, subset + (1 << counter), sum + superSet[counter], counter + 1);
            step(superSet, accumulator, subset, sum, counter + 1);
        }
    }

    static void printSubset(Subset e, Subset o) {
        String ret = "";
        for (int i = 0; i < 32; i++) {
            if (i % 2 == 0) {
                if ((1 & (e.subset >> (i / 2))) == 1) ret += " + " + set[i];
            }
            else {
                if ((1 & (o.subset >> (i / 2))) == 1) ret += " + " + set[i];
            }
        }
        if (ret.startsWith(" ")) ret = ret.substring(3) + " = " + (e.sum + o.sum);
        System.out.println(ret);
    }

    public static void main(String[] args) {
        int[][] superSets = split(set);

        step(superSets[0], evens, 0,0,0);
        step(superSets[1], odds, 0,0,0);

        for (Subset e : evens) {
            for (Subset o : odds) {
                if (e.sum + o.sum == target) printSubset(e, o);
            }
        }
    }
}

class Subset {
    int subset;
    int sum;

    Subset(int subset, int sum) {
        this.subset = subset;
        this.sum = sum;
    }
}

3

这类似于硬币找零问题

public class CoinCount 
{   
public static void main(String[] args)
{
    int[] coins={1,4,6,2,3,5};
    int count=0;

    for (int i=0;i<coins.length;i++)
    {
        count=count+Count(9,coins,i,0);
    }
    System.out.println(count);
}

public static int Count(int Sum,int[] coins,int index,int curSum)
{
    int count=0;

    if (index>=coins.length)
        return 0;

    int sumNow=curSum+coins[index];
    if (sumNow>Sum)
        return 0;
    if (sumNow==Sum)
        return 1;

    for (int i= index+1;i<coins.length;i++)
        count+=Count(Sum,coins,i,sumNow);

    return count;       
}
}

2

几年前,我使用C ++编写的表格使用了非常高效的算法。

如果设置PRINT 1,它将打印所有组合(但不会使用有效方法)。

它是如此高效,以至于它可以在不到10ms的时间内计算出超过10 ^ 14个组合。

#include <stdio.h>
#include <stdlib.h>
//#include "CTime.h"

#define SUM 300
#define MAXNUMsSIZE 30

#define PRINT 0


long long CountAddToSum(int,int[],int,const int[],int);
void printr(const int[], int);
long long table1[SUM][MAXNUMsSIZE];

int main()
{
    int Nums[]={3,4,5,6,7,9,13,11,12,13,22,35,17,14,18,23,33,54};
    int sum=SUM;
    int size=sizeof(Nums)/sizeof(int);
    int i,j,a[]={0};
    long long N=0;
    //CTime timer1;

    for(i=0;i<SUM;++i) 
        for(j=0;j<MAXNUMsSIZE;++j) 
            table1[i][j]=-1;

    N = CountAddToSum(sum,Nums,size,a,0); //algorithm
    //timer1.Get_Passd();

    //printf("\nN=%lld time=%.1f ms\n", N,timer1.Get_Passd());
    printf("\nN=%lld \n", N);
    getchar();
    return 1;
}

long long CountAddToSum(int s, int arr[],int arrsize, const int r[],int rsize)
{
    static int totalmem=0, maxmem=0;
    int i,*rnew;
    long long result1=0,result2=0;

    if(s<0) return 0;
    if (table1[s][arrsize]>0 && PRINT==0) return table1[s][arrsize];
    if(s==0)
    {
        if(PRINT) printr(r, rsize);
        return 1;
    }
    if(arrsize==0) return 0;

    //else
    rnew=(int*)malloc((rsize+1)*sizeof(int));

    for(i=0;i<rsize;++i) rnew[i]=r[i]; 
    rnew[rsize]=arr[arrsize-1];

    result1 =  CountAddToSum(s,arr,arrsize-1,rnew,rsize);
    result2 =  CountAddToSum(s-arr[arrsize-1],arr,arrsize,rnew,rsize+1);
    table1[s][arrsize]=result1+result2;
    free(rnew);

    return result1+result2;

}

void printr(const int r[], int rsize)
{
    int lastr=r[0],count=0,i;
    for(i=0; i<rsize;++i) 
    {
        if(r[i]==lastr)
            count++;
        else
        {
            printf(" %d*%d ",count,lastr);
            lastr=r[i];
            count=1;
        }
    }
    if(r[i-1]==lastr) printf(" %d*%d ",count,lastr);

    printf("\n");

}

嗨,您好!我需要执行以下操作的代码,才能在60个数字的列表中找到6个数字的所有可能和。总和应在最小180,最大191的范围内。是否可以对此代码进行调整?在哪里在云上运行该代码?我试图与Codenvy没有成功
defreturn

2

下面是Excel VBA版本。我需要在VBA中实现它(不是我的喜好,请不要判断我!),并使用此页面上的答案作为方法。我正在上传,以防其他人也需要VBA版本。

Option Explicit

Public Sub SumTarget()
    Dim numbers(0 To 6)  As Long
    Dim target As Long

    target = 15
    numbers(0) = 3: numbers(1) = 9: numbers(2) = 8: numbers(3) = 4: numbers(4) = 5
    numbers(5) = 7: numbers(6) = 10

    Call SumUpTarget(numbers, target)
End Sub

Public Sub SumUpTarget(numbers() As Long, target As Long)
    Dim part() As Long
    Call SumUpRecursive(numbers, target, part)
End Sub

Private Sub SumUpRecursive(numbers() As Long, target As Long, part() As Long)

    Dim s As Long, i As Long, j As Long, num As Long
    Dim remaining() As Long, partRec() As Long
    s = SumArray(part)

    If s = target Then Debug.Print "SUM ( " & ArrayToString(part) & " ) = " & target
    If s >= target Then Exit Sub

    If (Not Not numbers) <> 0 Then
        For i = 0 To UBound(numbers)
            Erase remaining()
            num = numbers(i)
            For j = i + 1 To UBound(numbers)
                AddToArray remaining, numbers(j)
            Next j
            Erase partRec()
            CopyArray partRec, part
            AddToArray partRec, num
            SumUpRecursive remaining, target, partRec
        Next i
    End If

End Sub

Private Function ArrayToString(x() As Long) As String
    Dim n As Long, result As String
    result = "{" & x(n)
    For n = LBound(x) + 1 To UBound(x)
        result = result & "," & x(n)
    Next n
    result = result & "}"
    ArrayToString = result
End Function

Private Function SumArray(x() As Long) As Long
    Dim n As Long
    SumArray = 0
    If (Not Not x) <> 0 Then
        For n = LBound(x) To UBound(x)
            SumArray = SumArray + x(n)
        Next n
    End If
End Function

Private Sub AddToArray(arr() As Long, x As Long)
    If (Not Not arr) <> 0 Then
        ReDim Preserve arr(0 To UBound(arr) + 1)
    Else
        ReDim Preserve arr(0 To 0)
    End If
    arr(UBound(arr)) = x
End Sub

Private Sub CopyArray(destination() As Long, source() As Long)
    Dim n As Long
    If (Not Not source) <> 0 Then
        For n = 0 To UBound(source)
                AddToArray destination, source(n)
        Next n
    End If
End Sub

输出(写入立即窗口)应为:

SUM ( {3,8,4} ) = 15
SUM ( {3,5,7} ) = 15
SUM ( {8,7} ) = 15
SUM ( {5,10} ) = 15 

2

这是具有更好的输出格式和C ++ 11功能的更好的版本:

void subset_sum_rec(std::vector<int> & nums, const int & target, std::vector<int> & partialNums) 
{
    int currentSum = std::accumulate(partialNums.begin(), partialNums.end(), 0);
    if (currentSum > target)
        return;
    if (currentSum == target) 
    {
        std::cout << "sum([";
        for (auto it = partialNums.begin(); it != std::prev(partialNums.end()); ++it)
            cout << *it << ",";
        cout << *std::prev(partialNums.end());
        std::cout << "])=" << target << std::endl;
    }
    for (auto it = nums.begin(); it != nums.end(); ++it) 
    {
        std::vector<int> remaining;
        for (auto it2 = std::next(it); it2 != nums.end(); ++it2)
            remaining.push_back(*it2);

        std::vector<int> partial = partialNums;
        partial.push_back(*it);
        subset_sum_rec(remaining, target, partial);
    }
}

2

Java非递归版本,该版本仅不断添加元素并在可能的值之间重新分配它们。0会被忽略,并且适用于固定列表(可以播放的内容)或可重复数字列表。

import java.util.*;

public class TestCombinations {

    public static void main(String[] args) {
        ArrayList<Integer> numbers = new ArrayList<>(Arrays.asList(0, 1, 2, 2, 5, 10, 20));
        LinkedHashSet<Integer> targets = new LinkedHashSet<Integer>() {{
            add(4);
            add(10);
            add(25);
        }};

        System.out.println("## each element can appear as many times as needed");
        for (Integer target: targets) {
            Combinations combinations = new Combinations(numbers, target, true);
            combinations.calculateCombinations();
            for (String solution: combinations.getCombinations()) {
                System.out.println(solution);
            }
        }

        System.out.println("## each element can appear only once");
        for (Integer target: targets) {
            Combinations combinations = new Combinations(numbers, target, false);
            combinations.calculateCombinations();
            for (String solution: combinations.getCombinations()) {
                System.out.println(solution);
            }
        }
    }

    public static class Combinations {
        private boolean allowRepetitions;
        private int[] repetitions;
        private ArrayList<Integer> numbers;
        private Integer target;
        private Integer sum;
        private boolean hasNext;
        private Set<String> combinations;

        /**
         * Constructor.
         *
         * @param numbers Numbers that can be used to calculate the sum.
         * @param target  Target value for sum.
         */
        public Combinations(ArrayList<Integer> numbers, Integer target) {
            this(numbers, target, true);
        }

        /**
         * Constructor.
         *
         * @param numbers Numbers that can be used to calculate the sum.
         * @param target  Target value for sum.
         */
        public Combinations(ArrayList<Integer> numbers, Integer target, boolean allowRepetitions) {
            this.allowRepetitions = allowRepetitions;
            if (this.allowRepetitions) {
                Set<Integer> numbersSet = new HashSet<>(numbers);
                this.numbers = new ArrayList<>(numbersSet);
            } else {
                this.numbers = numbers;
            }
            this.numbers.removeAll(Arrays.asList(0));
            Collections.sort(this.numbers);

            this.target = target;
            this.repetitions = new int[this.numbers.size()];
            this.combinations = new LinkedHashSet<>();

            this.sum = 0;
            if (this.repetitions.length > 0)
                this.hasNext = true;
            else
                this.hasNext = false;
        }

        /**
         * Calculate and return the sum of the current combination.
         *
         * @return The sum.
         */
        private Integer calculateSum() {
            this.sum = 0;
            for (int i = 0; i < repetitions.length; ++i) {
                this.sum += repetitions[i] * numbers.get(i);
            }
            return this.sum;
        }

        /**
         * Redistribute picks when only one of each number is allowed in the sum.
         */
        private void redistribute() {
            for (int i = 1; i < this.repetitions.length; ++i) {
                if (this.repetitions[i - 1] > 1) {
                    this.repetitions[i - 1] = 0;
                    this.repetitions[i] += 1;
                }
            }
            if (this.repetitions[this.repetitions.length - 1] > 1)
                this.repetitions[this.repetitions.length - 1] = 0;
        }

        /**
         * Get the sum of the next combination. When 0 is returned, there's no other combinations to check.
         *
         * @return The sum.
         */
        private Integer next() {
            if (this.hasNext && this.repetitions.length > 0) {
                this.repetitions[0] += 1;
                if (!this.allowRepetitions)
                    this.redistribute();
                this.calculateSum();

                for (int i = 0; i < this.repetitions.length && this.sum != 0; ++i) {
                    if (this.sum > this.target) {
                        this.repetitions[i] = 0;
                        if (i + 1 < this.repetitions.length) {
                            this.repetitions[i + 1] += 1;
                            if (!this.allowRepetitions)
                                this.redistribute();
                        }
                        this.calculateSum();
                    }
                }

                if (this.sum.compareTo(0) == 0)
                    this.hasNext = false;
            }
            return this.sum;
        }

        /**
         * Calculate all combinations whose sum equals target.
         */
        public void calculateCombinations() {
            while (this.hasNext) {
                if (this.next().compareTo(target) == 0)
                    this.combinations.add(this.toString());
            }
        }

        /**
         * Return all combinations whose sum equals target.
         *
         * @return Combinations as a set of strings.
         */
        public Set<String> getCombinations() {
            return this.combinations;
        }

        @Override
        public String toString() {
            StringBuilder stringBuilder = new StringBuilder("" + sum + ": ");
            for (int i = 0; i < repetitions.length; ++i) {
                for (int j = 0; j < repetitions[i]; ++j) {
                    stringBuilder.append(numbers.get(i) + " ");
                }
            }
            return stringBuilder.toString();
        }
    }
}

输入样例:

numbers: 0, 1, 2, 2, 5, 10, 20
targets: 4, 10, 25

样本输出:

## each element can appear as many times as needed
4: 1 1 1 1 
4: 1 1 2 
4: 2 2 
10: 1 1 1 1 1 1 1 1 1 1 
10: 1 1 1 1 1 1 1 1 2 
10: 1 1 1 1 1 1 2 2 
10: 1 1 1 1 2 2 2 
10: 1 1 2 2 2 2 
10: 2 2 2 2 2 
10: 1 1 1 1 1 5 
10: 1 1 1 2 5 
10: 1 2 2 5 
10: 5 5 
10: 10 
25: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 
25: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 
25: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 
25: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 
25: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 
25: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 
25: 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 
25: 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 
25: 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 
25: 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 
25: 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 
25: 1 1 1 2 2 2 2 2 2 2 2 2 2 2 
25: 1 2 2 2 2 2 2 2 2 2 2 2 2 
25: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 5 
25: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 5 
25: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 5 
25: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 5 
25: 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 5 
25: 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 5 
25: 1 1 1 1 1 1 1 1 2 2 2 2 2 2 5 
25: 1 1 1 1 1 1 2 2 2 2 2 2 2 5 
25: 1 1 1 1 2 2 2 2 2 2 2 2 5 
25: 1 1 2 2 2 2 2 2 2 2 2 5 
25: 2 2 2 2 2 2 2 2 2 2 5 
25: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 5 5 
25: 1 1 1 1 1 1 1 1 1 1 1 1 1 2 5 5 
25: 1 1 1 1 1 1 1 1 1 1 1 2 2 5 5 
25: 1 1 1 1 1 1 1 1 1 2 2 2 5 5 
25: 1 1 1 1 1 1 1 2 2 2 2 5 5 
25: 1 1 1 1 1 2 2 2 2 2 5 5 
25: 1 1 1 2 2 2 2 2 2 5 5 
25: 1 2 2 2 2 2 2 2 5 5 
25: 1 1 1 1 1 1 1 1 1 1 5 5 5 
25: 1 1 1 1 1 1 1 1 2 5 5 5 
25: 1 1 1 1 1 1 2 2 5 5 5 
25: 1 1 1 1 2 2 2 5 5 5 
25: 1 1 2 2 2 2 5 5 5 
25: 2 2 2 2 2 5 5 5 
25: 1 1 1 1 1 5 5 5 5 
25: 1 1 1 2 5 5 5 5 
25: 1 2 2 5 5 5 5 
25: 5 5 5 5 5 
25: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 10 
25: 1 1 1 1 1 1 1 1 1 1 1 1 1 2 10 
25: 1 1 1 1 1 1 1 1 1 1 1 2 2 10 
25: 1 1 1 1 1 1 1 1 1 2 2 2 10 
25: 1 1 1 1 1 1 1 2 2 2 2 10 
25: 1 1 1 1 1 2 2 2 2 2 10 
25: 1 1 1 2 2 2 2 2 2 10 
25: 1 2 2 2 2 2 2 2 10 
25: 1 1 1 1 1 1 1 1 1 1 5 10 
25: 1 1 1 1 1 1 1 1 2 5 10 
25: 1 1 1 1 1 1 2 2 5 10 
25: 1 1 1 1 2 2 2 5 10 
25: 1 1 2 2 2 2 5 10 
25: 2 2 2 2 2 5 10 
25: 1 1 1 1 1 5 5 10 
25: 1 1 1 2 5 5 10 
25: 1 2 2 5 5 10 
25: 5 5 5 10 
25: 1 1 1 1 1 10 10 
25: 1 1 1 2 10 10 
25: 1 2 2 10 10 
25: 5 10 10 
25: 1 1 1 1 1 20 
25: 1 1 1 2 20 
25: 1 2 2 20 
25: 5 20 
## each element can appear only once
4: 2 2 
10: 1 2 2 5 
10: 10 
25: 1 2 2 20 
25: 5 20

1

要使用excel查找组合-(相当简单)。(您的计算机一定不能太慢)

  1. 前往这个网站
  2. 转到“目标总和”页面
  3. 下载“总和到目标” excel文件。

    遵循网站页面上的指示。

希望这可以帮助。


1

Swift 3的Java解决方案转换:(通过@JeremyThompson)

protocol _IntType { }
extension Int: _IntType {}


extension Array where Element: _IntType {

    func subsets(to: Int) -> [[Element]]? {

        func sum_up_recursive(_ numbers: [Element], _ target: Int, _ partial: [Element], _ solution: inout [[Element]]) {

            var sum: Int = 0
            for x in partial {
                sum += x as! Int
            }

            if sum == target {
                solution.append(partial)
            }

            guard sum < target else {
                return
            }

            for i in stride(from: 0, to: numbers.count, by: 1) {

                var remaining = [Element]()

                for j in stride(from: i + 1, to: numbers.count, by: 1) {
                    remaining.append(numbers[j])
                }

                var partial_rec = [Element](partial)
                partial_rec.append(numbers[i])

                sum_up_recursive(remaining, target, partial_rec, &solution)
            }
        }

        var solutions = [[Element]]()
        sum_up_recursive(self, to, [Element](), &solutions)

        return solutions.count > 0 ? solutions : nil
    }

}

用法:

let numbers = [3, 9, 8, 4, 5, 7, 10]

if let solution = numbers.subsets(to: 15) {
    print(solution) // output: [[3, 8, 4], [3, 5, 7], [8, 7], [5, 10]]
} else {
    print("not possible")
}

1

这也可以用于打印所有答案

public void recur(int[] a, int n, int sum, int[] ans, int ind) {
    if (n < 0 && sum != 0)
        return;
    if (n < 0 && sum == 0) {
        print(ans, ind);
        return;
    }
    if (sum >= a[n]) {
        ans[ind] = a[n];
        recur(a, n - 1, sum - a[n], ans, ind + 1);
    }
    recur(a, n - 1, sum, ans, ind);
}

public void print(int[] a, int n) {
    for (int i = 0; i < n; i++)
        System.out.print(a[i] + " ");
    System.out.println();
}

时间复杂度是指数级的。2 ^ n的阶数


1

我正在为scala作业做类似的事情。想在这里发布我的解决方案:

 def countChange(money: Int, coins: List[Int]): Int = {
      def getCount(money: Int, remainingCoins: List[Int]): Int = {
        if(money == 0 ) 1
        else if(money < 0 || remainingCoins.isEmpty) 0
        else
          getCount(money, remainingCoins.tail) +
            getCount(money - remainingCoins.head, remainingCoins)
      }
      if(money == 0 || coins.isEmpty) 0
      else getCount(money, coins)
    }

1

我将C#示例移植到了Objective-c,但没有在响应中看到它:

//Usage
NSMutableArray* numberList = [[NSMutableArray alloc] init];
NSMutableArray* partial = [[NSMutableArray alloc] init];
int target = 16;
for( int i = 1; i<target; i++ )
{ [numberList addObject:@(i)]; }
[self findSums:numberList target:target part:partial];


//*******************************************************************
// Finds combinations of numbers that add up to target recursively
//*******************************************************************
-(void)findSums:(NSMutableArray*)numbers target:(int)target part:(NSMutableArray*)partial
{
    int s = 0;
    for (NSNumber* x in partial)
    { s += [x intValue]; }

    if (s == target)
    { NSLog(@"Sum[%@]", partial); }

    if (s >= target)
    { return; }

    for (int i = 0;i < [numbers count];i++ )
    {
        int n = [numbers[i] intValue];
        NSMutableArray* remaining = [[NSMutableArray alloc] init];
        for (int j = i + 1; j < [numbers count];j++)
        { [remaining addObject:@([numbers[j] intValue])]; }

        NSMutableArray* partRec = [[NSMutableArray alloc] initWithArray:partial];
        [partRec addObject:@(n)];
        [self findSums:remaining target:target part:partRec];
    }
}

1

@KeithBeller的答案带有稍微更改的变量名称和一些注释。

    public static void Main(string[] args)
    {
        List<int> input = new List<int>() { 3, 9, 8, 4, 5, 7, 10 };
        int targetSum = 15;
        SumUp(input, targetSum);
    }

    public static void SumUp(List<int> input, int targetSum)
    {
        SumUpRecursive(input, targetSum, new List<int>());
    }

    private static void SumUpRecursive(List<int> remaining, int targetSum, List<int> listToSum)
    {
        // Sum up partial
        int sum = 0;
        foreach (int x in listToSum)
            sum += x;

        //Check sum matched
        if (sum == targetSum)
            Console.WriteLine("sum(" + string.Join(",", listToSum.ToArray()) + ")=" + targetSum);

        //Check sum passed
        if (sum >= targetSum)
            return;

        //Iterate each input character
        for (int i = 0; i < remaining.Count; i++)
        {
            //Build list of remaining items to iterate
            List<int> newRemaining = new List<int>();
            for (int j = i + 1; j < remaining.Count; j++)
                newRemaining.Add(remaining[j]);

            //Update partial list
            List<int> newListToSum = new List<int>(listToSum);
            int currentItem = remaining[i];
            newListToSum.Add(currentItem);
            SumUpRecursive(newRemaining, targetSum, newListToSum);
        }
    }'

1

PHP版本受Keith Beller的C#版本启发的版本。

bala的PHP版本对我不起作用,因为我不需要对数字进行分组。我想要一个带有一个目标值和一组数字的更简单的实现。此功能还将删除任何重复的条目。

/**
 * Calculates a subset sum: finds out which combinations of numbers
 * from the numbers array can be added together to come to the target
 * number.
 * 
 * Returns an indexed array with arrays of number combinations.
 * 
 * Example: 
 * 
 * <pre>
 * $matches = subset_sum(array(5,10,7,3,20), 25);
 * </pre>
 * 
 * Returns:
 * 
 * <pre>
 * Array
 * (
 *   [0] => Array
 *   (
 *       [0] => 3
 *       [1] => 5
 *       [2] => 7
 *       [3] => 10
 *   )
 *   [1] => Array
 *   (
 *       [0] => 5
 *       [1] => 20
 *   )
 * )
 * </pre>
 * 
 * @param number[] $numbers
 * @param number $target
 * @param array $part
 * @return array[number[]]
 */
function subset_sum($numbers, $target, $part=null)
{
    // we assume that an empty $part variable means this
    // is the top level call.
    $toplevel = false;
    if($part === null) {
        $toplevel = true;
        $part = array();
    }

    $s = 0;
    foreach($part as $x) 
    {
        $s = $s + $x;
    }

    // we have found a match!
    if($s == $target) 
    {
        sort($part); // ensure the numbers are always sorted
        return array(implode('|', $part));
    }

    // gone too far, break off
    if($s >= $target) 
    {
        return null;
    }

    $matches = array();
    $totalNumbers = count($numbers);

    for($i=0; $i < $totalNumbers; $i++) 
    {
        $remaining = array();
        $n = $numbers[$i];

        for($j = $i+1; $j < $totalNumbers; $j++) 
        {
            $remaining[] = $numbers[$j];
        }

        $part_rec = $part;
        $part_rec[] = $n;

        $result = subset_sum($remaining, $target, $part_rec);
        if($result) 
        {
            $matches = array_merge($matches, $result);
        }
    }

    if(!$toplevel) 
    {
        return $matches;
    }

    // this is the top level function call: we have to
    // prepare the final result value by stripping any
    // duplicate results.
    $matches = array_unique($matches);
    $result = array();
    foreach($matches as $entry) 
    {
        $result[] = explode('|', $entry);
    }

    return $result;
}

1

推荐作为答案:

这是使用es2015 generators的解决方案:

function* subsetSum(numbers, target, partial = [], partialSum = 0) {

  if(partialSum === target) yield partial

  if(partialSum >= target) return

  for(let i = 0; i < numbers.length; i++){
    const remaining = numbers.slice(i + 1)
        , n = numbers[i]

    yield* subsetSum(remaining, target, [...partial, n], partialSum + n)
  }

}

实际上,使用生成器非常有用,因为它使您可以在找到有效子集后立即暂停脚本执行。这与没有生成器(即缺少状态)的解决方案形成对比,该生成器必须遍历的每个子集numbers


1

首先推导0。零是加法的标识,因此在这种特殊情况下,根据半规半截式定律,它是无用的。如果您想爬升至正数,还可以推导负数。否则,您还需要减法运算。

所以...在此特定工作上可获得的最快算法如下JS中给出的。

function items2T([n,...ns],t){
    var c = ~~(t/n);
    return ns.length ? Array(c+1).fill()
                                 .reduce((r,_,i) => r.concat(items2T(ns, t-n*i).map(s => Array(i).fill(n).concat(s))),[])
                     : t % n ? []
                             : [Array(c).fill(n)];
};

var data = [3, 9, 8, 4, 5, 7, 10],
    result;

console.time("combos");
result = items2T(data, 15);
console.timeEnd("combos");
console.log(JSON.stringify(result));

这是一种非常快速的算法,但是如果对data数组降序排序,它将更快。使用.sort()是微不足道的,因为该算法将结束与少递归调用。


真好 它表明您是一位经验丰富的程序员:)
James P.

1

Perl版本(最佳答案):

use strict;

sub subset_sum {
  my ($numbers, $target, $result, $sum) = @_;

  print 'sum('.join(',', @$result).") = $target\n" if $sum == $target;
  return if $sum >= $target;

  subset_sum([@$numbers[$_ + 1 .. $#$numbers]], $target, 
             [@{$result||[]}, $numbers->[$_]], $sum + $numbers->[$_])
    for (0 .. $#$numbers);
}

subset_sum([3,9,8,4,5,7,10,6], 15);

结果:

sum(3,8,4) = 15
sum(3,5,7) = 15
sum(9,6) = 15
sum(8,7) = 15
sum(4,5,6) = 15
sum(5,10) = 15

JavaScript版本:

const subsetSum = (numbers, target, partial = [], sum = 0) => {
  if (sum < target)
    numbers.forEach((num, i) =>
      subsetSum(numbers.slice(i + 1), target, partial.concat([num]), sum + num));
  else if (sum == target)
    console.log('sum(%s) = %s', partial.join(), target);
}

subsetSum([3,9,8,4,5,7,10,6], 15);

实际返回结果(而不是打印结果)的JavaScript一线式:

const subsetSum=(n,t,p=[],s=0,r=[])=>(s<t?n.forEach((l,i)=>subsetSum(n.slice(i+1),t,[...p,l],s+l,r)):s==t?r.push(p):0,r);

console.log(subsetSum([3,9,8,4,5,7,10,6], 15));

我最喜欢的带回调的一线式:

const subsetSum=(n,t,cb,p=[],s=0)=>s<t?n.forEach((l,i)=>subsetSum(n.slice(i+1),t,cb,[...p,l],s+l)):s==t?cb(p):0;

subsetSum([3,9,8,4,5,7,10,6], 15, console.log);


0
function solve(n){
    let DP = [];

     DP[0] = DP[1] = DP[2] = 1;
     DP[3] = 2;

    for (let i = 4; i <= n; i++) {
      DP[i] = DP[i-1] + DP[i-3] + DP[i-4];
    }
    return DP[n]
}

console.log(solve(5))

这是一个针对JS的动态解决方案,用于说明任何人可以获得多少总和的方法。如果您考虑时间和空间的复杂性,这可能是正确的解决方案。


0
import java.util.*;

public class Main{

     int recursionDepth = 0;
     private int[][] memo;

     public static void main(String []args){
         int[] nums = new int[] {5,2,4,3,1};
         int N = nums.length;
         Main main =  new Main();
         main.memo = new int[N+1][N+1];
         main._findCombo(0, N-1,nums, 8, 0, new LinkedList() );
         System.out.println(main.recursionDepth);
     }


       private void _findCombo(
           int from,
           int to,
           int[] nums,
           int targetSum,
           int currentSum,
           LinkedList<Integer> list){

            if(memo[from][to] != 0) {
                currentSum = currentSum + memo[from][to];
            }

            if(currentSum > targetSum) {
                return;
            }

            if(currentSum ==  targetSum) {
                System.out.println("Found - " +list);
                return;
            }

            recursionDepth++;

           for(int i= from ; i <= to; i++){
               list.add(nums[i]);
               memo[from][i] = currentSum + nums[i];
               _findCombo(i+1, to,nums, targetSum, memo[from][i], list);
                list.removeLast();
           }

     }
}

0

我不喜欢Javascript解决方案,我看到了为什么我要使用部分应用,闭包和递归为自己构建一个Javascript解决方案:

好的,我主要担心的是组合数组是否可以满足需求目标,但是通过这种方法,您可以开始查找其余的组合

在这里,只需设置目标并传递组合数组即可。

function main() {
    const target = 10
    const getPermutationThatSumT = setTarget(target)
    const permutation = getPermutationThatSumT([1, 4, 2, 5, 6, 7])

    console.log( permutation );
}

我想出的当前实现

function setTarget(target) {
    let partial = [];

    return function permute(input) {
        let i, removed;
        for (i = 0; i < input.length; i++) {
            removed = input.splice(i, 1)[0];
            partial.push(removed);

            const sum = partial.reduce((a, b) => a + b)
            if (sum === target) return partial.slice()
            if (sum < target) permute(input)

            input.splice(i, 0, removed);
            partial.pop();
        }
        return null
    };
}
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