I found a piece of code that I was writing for interview prep few months ago.
According to the comment I had, it was trying to solve this problem:
Given some dollar value in cents (e.g. 200 = 2 dollars, 1000 = 10 dollars), find all the combinations of coins that make up the dollar value. There are only pennies (1¢), nickels (5¢), dimes (10¢), and quarters (25¢) allowed.
For example, if 100 was given, the answer should be:
4 quarter(s) 0 dime(s) 0 nickel(s) 0 pennies
3 quarter(s) 1 dime(s) 0 nickel(s) 15 pennies
etc.
I believe that this can be solved in both iterative and recursive ways. My recursive solution is quite buggy, and I was wondering how other people would solve this problem. The difficult part of this problem was making it as efficient as possible.
This question is related to
algorithm
recursion
puzzle
coin-change
The answer is
Let C(i,J) the set of combinations of making i cents using the values in the set J.
You can define C as that:
(first(J) takes in a deterministic way an element of a set)
It turns out a pretty recursive function... and reasonably efficient if you use memoization ;)
In Scala Programming language i would do it like this:
def countChange(money: Int, coins: List[Int]): Int = {
money match {
case 0 => 1
case x if x < 0 => 0
case x if x >= 1 && coins.isEmpty => 0
case _ => countChange(money, coins.tail) + countChange(money - coins.head, coins)
}
}
# short and sweet with O(n) table memory
#include <iostream>
#include <vector>
int count( std::vector<int> s, int n )
{
std::vector<int> table(n+1,0);
table[0] = 1;
for ( auto& k : s )
for(int j=k; j<=n; ++j)
table[j] += table[j-k];
return table[n];
}
int main()
{
std::cout << count({25, 10, 5, 1}, 100) << std::endl;
return 0;
}
/*
* make a list of all distinct sets of coins of from the set of coins to
* sum up to the given target amount.
* Here the input set of coins is assumed yo be {1, 2, 4}, this set MUST
* have the coins sorted in ascending order.
* Outline of the algorithm:
*
* Keep track of what the current coin is, say ccn; current number of coins
* in the partial solution, say k; current sum, say sum, obtained by adding
* ccn; sum sofar, say accsum:
* 1) Use ccn as long as it can be added without exceeding the target
* a) if current sum equals target, add cc to solution coin set, increase
* coin coin in the solution by 1, and print it and return
* b) if current sum exceeds target, ccn can't be in the solution, so
* return
* c) if neither of the above, add current coin to partial solution,
* increase k by 1 (number of coins in partial solution), and recuse
* 2) When current denomination can no longer be used, start using the
* next higher denomination coins, just like in (1)
* 3) When all denominations have been used, we are done
*/
#include <iostream>
#include <cstdlib>
using namespace std;
// int num_calls = 0;
// int num_ways = 0;
void print(const int coins[], int n);
void combine_coins(
const int denoms[], // coins sorted in ascending order
int n, // number of denominations
int target, // target sum
int accsum, // accumulated sum
int coins[], // solution set, MUST equal
// target / lowest denom coin
int k // number of coins in coins[]
)
{
int ccn; // current coin
int sum; // current sum
// ++num_calls;
for (int i = 0; i < n; ++i) {
/*
* skip coins of lesser denomination: This is to be efficient
* and also avoid generating duplicate sequences. What we need
* is combinations and without this check we will generate
* permutations.
*/
if (k > 0 && denoms[i] < coins[k - 1])
continue; // skip coins of lesser denomination
ccn = denoms[i];
if ((sum = accsum + ccn) > target)
return; // no point trying higher denominations now
if (sum == target) {
// found yet another solution
coins[k] = ccn;
print(coins, k + 1);
// ++num_ways;
return;
}
coins[k] = ccn;
combine_coins(denoms, n, target, sum, coins, k + 1);
}
}
void print(const int coins[], int n)
{
int s = 0;
for (int i = 0; i < n; ++i) {
cout << coins[i] << " ";
s += coins[i];
}
cout << "\t = \t" << s << "\n";
}
int main(int argc, const char *argv[])
{
int denoms[] = {1, 2, 4};
int dsize = sizeof(denoms) / sizeof(denoms[0]);
int target;
if (argv[1])
target = atoi(argv[1]);
else
target = 8;
int *coins = new int[target];
combine_coins(denoms, dsize, target, 0, coins, 0);
// cout << "num calls = " << num_calls << ", num ways = " << num_ways << "\n";
return 0;
}
Here's a C# function:
public static void change(int money, List<int> coins, List<int> combination)
{
if(money < 0 || coins.Count == 0) return;
if (money == 0)
{
Console.WriteLine((String.Join("; ", combination)));
return;
}
List<int> copy = new List<int>(coins);
copy.RemoveAt(0);
change(money, copy, combination);
combination = new List<int>(combination) { coins[0] };
change(money - coins[0], coins, new List<int>(combination));
}
Use it like this:
change(100, new List<int>() {5, 10, 25}, new List<int>());
It prints:
25; 25; 25; 25
10; 10; 10; 10; 10; 25; 25
10; 10; 10; 10; 10; 10; 10; 10; 10; 10
5; 10; 10; 25; 25; 25
5; 10; 10; 10; 10; 10; 10; 10; 25
5; 5; 10; 10; 10; 10; 25; 25
5; 5; 10; 10; 10; 10; 10; 10; 10; 10; 10
5; 5; 5; 10; 25; 25; 25
5; 5; 5; 10; 10; 10; 10; 10; 10; 25
5; 5; 5; 5; 10; 10; 10; 25; 25
5; 5; 5; 5; 10; 10; 10; 10; 10; 10; 10; 10
5; 5; 5; 5; 5; 25; 25; 25
5; 5; 5; 5; 5; 10; 10; 10; 10; 10; 25
5; 5; 5; 5; 5; 5; 10; 10; 25; 25
5; 5; 5; 5; 5; 5; 10; 10; 10; 10; 10; 10; 10
5; 5; 5; 5; 5; 5; 5; 10; 10; 10; 10; 25
5; 5; 5; 5; 5; 5; 5; 5; 10; 25; 25
5; 5; 5; 5; 5; 5; 5; 5; 10; 10; 10; 10; 10; 10
5; 5; 5; 5; 5; 5; 5; 5; 5; 10; 10; 10; 25
5; 5; 5; 5; 5; 5; 5; 5; 5; 5; 25; 25
5; 5; 5; 5; 5; 5; 5; 5; 5; 5; 10; 10; 10; 10; 10
5; 5; 5; 5; 5; 5; 5; 5; 5; 5; 5; 10; 10; 25
5; 5; 5; 5; 5; 5; 5; 5; 5; 5; 5; 5; 10; 10; 10; 10
5; 5; 5; 5; 5; 5; 5; 5; 5; 5; 5; 5; 5; 10; 25
5; 5; 5; 5; 5; 5; 5; 5; 5; 5; 5; 5; 5; 5; 10; 10; 10
5; 5; 5; 5; 5; 5; 5; 5; 5; 5; 5; 5; 5; 5; 5; 25
5; 5; 5; 5; 5; 5; 5; 5; 5; 5; 5; 5; 5; 5; 5; 5; 10; 10
5; 5; 5; 5; 5; 5; 5; 5; 5; 5; 5; 5; 5; 5; 5; 5; 5; 5; 10
5; 5; 5; 5; 5; 5; 5; 5; 5; 5; 5; 5; 5; 5; 5; 5; 5; 5; 5; 5
Here's some absolutely straightforward C++ code to solve the problem which did ask for all the combinations to be shown.
#include <stdio.h>
#include <stdlib.h>
int main(int argc, char *argv[])
{
if (argc != 2)
{
printf("usage: change amount-in-cents\n");
return 1;
}
int total = atoi(argv[1]);
printf("quarter\tdime\tnickle\tpenny\tto make %d\n", total);
int combos = 0;
for (int q = 0; q <= total / 25; q++)
{
int total_less_q = total - q * 25;
for (int d = 0; d <= total_less_q / 10; d++)
{
int total_less_q_d = total_less_q - d * 10;
for (int n = 0; n <= total_less_q_d / 5; n++)
{
int p = total_less_q_d - n * 5;
printf("%d\t%d\t%d\t%d\n", q, d, n, p);
combos++;
}
}
}
printf("%d combinations\n", combos);
return 0;
}
But I'm quite intrigued about the sub problem of just calculating the number of combinations. I suspect there's a closed-form equation for it.
Java solution
import java.util.Arrays;
import java.util.Scanner;
public class nCents {
public static void main(String[] args) {
Scanner input=new Scanner(System.in);
int cents=input.nextInt();
int num_ways [][] =new int [5][cents+1];
//putting in zeroes to offset
int getCents[]={0 , 0 , 5 , 10 , 25};
Arrays.fill(num_ways[0], 0);
Arrays.fill(num_ways[1], 1);
int current_cent=0;
for(int i=2;i<num_ways.length;i++){
current_cent=getCents[i];
for(int j=1;j<num_ways[0].length;j++){
if(j-current_cent>=0){
if(j-current_cent==0){
num_ways[i][j]=num_ways[i-1][j]+1;
}else{
num_ways[i][j]=num_ways[i][j-current_cent]+num_ways[i-1][j];
}
}else{
num_ways[i][j]=num_ways[i-1][j];
}
}
}
System.out.println(num_ways[num_ways.length-1][num_ways[0].length-1]);
}
}
Note: This only shows the number of ways.
Scala function:
def countChange(money: Int, coins: List[Int]): Int =
if (money == 0) 1
else if (coins.isEmpty || money < 0) 0
else countChange(money - coins.head, coins) + countChange(money, coins.tail)
I used a really simple loop to solve this in a BlackJack game I'm writing in HTML5 using the Isogenic Game Engine. You can see a video of the BlackJack game which shows the chips that were used to make up a bet from the bet value on the BlackJack table above the cards: http://bit.ly/yUF6iw
In this example, betValue equals the total value that you wish to divide into "coins" or "chips" or whatever.
You can set the chipValues array items to whatever your coins or chips are worth. Make sure that the items are ordered from lowest value to highest value (penny, nickel, dime, quarter).
Here is the JavaScript:
// Set the total that we want to divide into chips
var betValue = 191;
// Set the chip values
var chipValues = [
1,
5,
10,
25
];
// Work out how many of each chip is required to make up the bet value
var tempBet = betValue;
var tempChips = [];
for (var i = chipValues.length - 1; i >= 0; i--) {
var chipValue = chipValues[i];
var divided = Math.floor(tempBet / chipValue);
if (divided >= 1) {
tempChips[i] = divided;
tempBet -= divided * chipValues[i];
}
if (tempBet == 0) { break; }
}
// Display the chips and how many of each make up the betValue
for (var i in tempChips) {
console.log(tempChips[i] + ' of ' + chipValues[i]);
}
You obviously don't need to do the last loop and it is only there to console.log the final array values.
I know this is a very old question. I was searching through the proper answer and couldn't find anything that is simple and satisfactory. Took me some time but was able to jot down something.
function denomination(coins, original_amount){
var original_amount = original_amount;
var original_best = [ ];
for(var i=0;i<coins.length; i++){
var amount = original_amount;
var best = [ ];
var tempBest = [ ]
while(coins[i]<=amount){
amount = amount - coins[i];
best.push(coins[i]);
}
if(amount>0 && coins.length>1){
tempBest = denomination(coins.slice(0,i).concat(coins.slice(i+1,coins.length)), amount);
//best = best.concat(denomination(coins.splice(i,1), amount));
}
if(tempBest.length!=0 || (best.length!=0 && amount==0)){
best = best.concat(tempBest);
if(original_best.length==0 ){
original_best = best
}else if(original_best.length > best.length ){
original_best = best;
}
}
}
return original_best;
}
denomination( [1,10,3,9] , 19 );
This is a javascript solution and uses recursion.
Scala function :
def countChange(money: Int, coins: List[Int]): Int = {
def loop(money: Int, lcoins: List[Int], count: Int): Int = {
// if there are no more coins or if we run out of money ... return 0
if ( lcoins.isEmpty || money < 0) 0
else{
if (money == 0 ) count + 1
/* if the recursive subtraction leads to 0 money left - a prefect division hence return count +1 */
else
/* keep iterating ... sum over money and the rest of the coins and money - the first item and the full set of coins left*/
loop(money, lcoins.tail,count) + loop(money - lcoins.head,lcoins, count)
}
}
val x = loop(money, coins, 0)
Console println x
x
}
This is a simple recursive algorithm that takes a bill, then takes a smaller bill recursively until it reaches the sum, it then takes another bill of same denomination, and recurses again. See sample output below for illustration.
var bills = new int[] { 100, 50, 20, 10, 5, 1 };
void PrintAllWaysToMakeChange(int sumSoFar, int minBill, string changeSoFar)
{
for (int i = minBill; i < bills.Length; i++)
{
var change = changeSoFar;
var sum = sumSoFar;
while (sum > 0)
{
if (!string.IsNullOrEmpty(change)) change += " + ";
change += bills[i];
sum -= bills[i];
if (sum > 0)
{
PrintAllWaysToMakeChange(sum, i + 1, change);
}
}
if (sum == 0)
{
Console.WriteLine(change);
}
}
}
PrintAllWaysToMakeChange(15, 0, "");
Prints the following:
10 + 5
10 + 1 + 1 + 1 + 1 + 1
5 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1
5 + 5 + 1 + 1 + 1 + 1 + 1
5 + 5 + 5
1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1 + 1
The code is using Java to solve this problem and it also works... This method may not be a good idea because of too many loops, but it's really a straight forward way.
public class RepresentCents {
public static int sum(int n) {
int count = 0;
for (int i = 0; i <= n / 25; i++) {
for (int j = 0; j <= n / 10; j++) {
for (int k = 0; k <= n / 5; k++) {
for (int l = 0; l <= n; l++) {
int v = i * 25 + j * 10 + k * 5 + l;
if (v == n) {
count++;
} else if (v > n) {
break;
}
}
}
}
}
return count;
}
public static void main(String[] args) {
System.out.println(sum(100));
}
}
I would favor a recursive solution. You have some list of denominations, if the smallest one can evenly divide any remaining currency amount, this should work fine.
Basically, you move from largest to smallest denominations.
Recursively,
- You have a current total to fill, and a largest denomination (with more than 1 left). If there is only 1 denomination left, there is only one way to fill the total. You can use 0 to k copies of your current denomination such that k * cur denomination <= total.
- For 0 to k, call the function with the modified total and new largest denomination.
- Add up the results from 0 to k. That's how many ways you can fill your total from the current denomination on down. Return this number.
Here's my python version of your stated problem, for 200 cents. I get 1463 ways. This version prints all the combinations and the final count total.
#!/usr/bin/python
# find the number of ways to reach a total with the given number of combinations
cents = 200
denominations = [25, 10, 5, 1]
names = {25: "quarter(s)", 10: "dime(s)", 5 : "nickel(s)", 1 : "pennies"}
def count_combs(left, i, comb, add):
if add: comb.append(add)
if left == 0 or (i+1) == len(denominations):
if (i+1) == len(denominations) and left > 0:
if left % denominations[i]:
return 0
comb.append( (left/denominations[i], demoninations[i]) )
i += 1
while i < len(denominations):
comb.append( (0, denominations[i]) )
i += 1
print(" ".join("%d %s" % (n,names[c]) for (n,c) in comb))
return 1
cur = denominations[i]
return sum(count_combs(left-x*cur, i+1, comb[:], (x,cur)) for x in range(0, int(left/cur)+1))
count_combs(cents, 0, [], None)
var countChange = function (money,coins) {
function countChangeSub(money,coins,n) {
if(money==0) return 1;
if(money<0 || coins.length ==n) return 0;
return countChangeSub(money-coins[n],coins,n) + countChangeSub(money,coins,n+1);
}
return countChangeSub(money,coins,0);
}
The below java solution which will print the different combinations as well. Easy to understand. Idea is
for sum 5
The solution is
5 - 5(i) times 1 = 0
if(sum = 0)
print i times 1
5 - 4(i) times 1 = 1
5 - 3 times 1 = 2
2 - 1(j) times 2 = 0
if(sum = 0)
print i times 1 and j times 2
and so on......
If the remaining sum in each loop is lesser than the denomination ie if remaining sum 1 is lesser than 2, then just break the loop
The complete code below
Please correct me in case of any mistakes
public class CoinCombinbationSimple {
public static void main(String[] args) {
int sum = 100000;
printCombination(sum);
}
static void printCombination(int sum) {
for (int i = sum; i >= 0; i--) {
int sumCopy1 = sum - i * 1;
if (sumCopy1 == 0) {
System.out.println(i + " 1 coins");
}
for (int j = sumCopy1 / 2; j >= 0; j--) {
int sumCopy2 = sumCopy1;
if (sumCopy2 < 2) {
break;
}
sumCopy2 = sumCopy1 - 2 * j;
if (sumCopy2 == 0) {
System.out.println(i + " 1 coins " + j + " 2 coins ");
}
for (int k = sumCopy2 / 5; k >= 0; k--) {
int sumCopy3 = sumCopy2;
if (sumCopy2 < 5) {
break;
}
sumCopy3 = sumCopy2 - 5 * k;
if (sumCopy3 == 0) {
System.out.println(i + " 1 coins " + j + " 2 coins "
+ k + " 5 coins");
}
}
}
}
}
}
Lots of variations here but couldn't find a PHP solution for the number of combinations anywhere so I'll add one in.
/**
* @param int $money The total value
* @param array $coins The coin denominations
* @param int $sum The countable sum
* @return int
*/
function getTotalCombinations($money, $coins, &$sum = 0){
if ($money == 0){
return $sum++;
} else if (empty($coins) || $money < 0){
return $sum;
} else {
$firstCoin = array_pop(array_reverse($coins));
getTotalCombinations($money - $firstCoin, $coins, $sum) + getTotalCombinations($money, array_diff($coins, [$firstCoin]), $sum);
}
return $sum;
}
$totalCombinations = getTotalCombinations($money, $coins);
I found this neat piece of code in the book "Python For Data Analysis" by O'reily. It uses lazy implementation and int comparison and i presume it can be modified for other denominations using decimals. Let me know how it works for you!
def make_change(amount, coins=[1, 5, 10, 25], hand=None):_x000D_
hand = [] if hand is None else hand_x000D_
if amount == 0:_x000D_
yield hand_x000D_
for coin in coins:_x000D_
# ensures we don't give too much change, and combinations are unique_x000D_
if coin > amount or (len(hand) > 0 and hand[-1] < coin):_x000D_
continue_x000D_
for result in make_change(amount - coin, coins=coins,_x000D_
hand=hand + [coin]):_x000D_
yield resultpublic class Coins {
static int ac = 421;
static int bc = 311;
static int cc = 11;
static int target = 4000;
public static void main(String[] args) {
method2();
}
public static void method2(){
//running time n^2
int da = target/ac;
int db = target/bc;
for(int i=0;i<=da;i++){
for(int j=0;j<=db;j++){
int rem = target-(i*ac+j*bc);
if(rem < 0){
break;
}else{
if(rem%cc==0){
System.out.format("\n%d, %d, %d ---- %d + %d + %d = %d \n", i, j, rem/cc, i*ac, j*bc, (rem/cc)*cc, target);
}
}
}
}
}
}
The following one-liner in Mathematica produces the desired result
parts[n_]:=Flatten[Table[{(n-i)/25,(i-j)/10,(j-k)/5,k},{i,n,0,-25},{j,i,0,-10},{k,j,0,-5}],2]
The table trivially builds up all combinations by iterating through all ways of how many coins of a bigger kind fit into n, while repeating the same steps with coins of smaller kind for the remainder. The implementation should be similarly trivial in any other programming language.
The output is a list of elements with the notation:
{number of quarters, number of dimes, number of nickels, number of cents}
The intuition behind the construction can be read off of an example:
parts[51]
Here is a python based solution that uses recursion as well as memoization resulting in a complexity of O(mxn)
def get_combinations_dynamic(self, amount, coins, memo): end_index = len(coins) - 1 memo_key = str(amount)+'->'+str(coins) if memo_key in memo: return memo[memo_key] remaining_amount = amount if amount < 0: return [] if amount == 0: return [[]] combinations = [] if len(coins) <= 1: if amount % coins[0] == 0: combination = [] for i in range(amount // coins[0]): combination.append(coins[0]) list.sort(combination) if combination not in combinations: combinations.append(combination) else: k = 0 while remaining_amount >= 0: sub_combinations = self.get_combinations_dynamic(remaining_amount, coins[:end_index], memo) for combination in sub_combinations: temp = combination[:] for i in range(k): temp.append(coins[end_index]) list.sort(temp) if temp not in combinations: combinations.append(temp) k += 1 remaining_amount -= coins[end_index] memo[memo_key] = combinations return combinations
This blog entry of mine solves this knapsack like problem for the figures from an XKCD comic. A simple change to the items dict and the exactcost value will yield all solutions for your problem too.
If the problem were to find the change that used the least cost, then a naive greedy algorithm that used as much of the highest value coin might well fail for some combinations of coins and target amount. For example if there are coins with values 1, 3, and 4; and the target amount is 6 then the greedy algorithm might suggest three coins of value 4, 1, and 1 when it is easy to see that you could use two coins each of value 3.
- Paddy.
Straightforward java solution:
public static void main(String[] args)
{
int[] denoms = {4,2,3,1};
int[] vals = new int[denoms.length];
int target = 6;
printCombinations(0, denoms, target, vals);
}
public static void printCombinations(int index, int[] denom,int target, int[] vals)
{
if(target==0)
{
System.out.println(Arrays.toString(vals));
return;
}
if(index == denom.length) return;
int currDenom = denom[index];
for(int i = 0; i*currDenom <= target;i++)
{
vals[index] = i;
printCombinations(index+1, denom, target - i*currDenom, vals);
vals[index] = 0;
}
}
This is a really old question, but I came up with a recursive solution in java that seemed smaller than all the others, so here goes -
public static void printAll(int ind, int[] denom,int N,int[] vals){
if(N==0){
System.out.println(Arrays.toString(vals));
return;
}
if(ind == (denom.length))return;
int currdenom = denom[ind];
for(int i=0;i<=(N/currdenom);i++){
vals[ind] = i;
printAll(ind+1,denom,N-i*currdenom,vals);
}
}
Improvements:
public static void printAllCents(int ind, int[] denom,int N,int[] vals){
if(N==0){
if(ind < denom.length) {
for(int i=ind;i<denom.length;i++)
vals[i] = 0;
}
System.out.println(Arrays.toString(vals));
return;
}
if(ind == (denom.length)) {
vals[ind-1] = 0;
return;
}
int currdenom = denom[ind];
for(int i=0;i<=(N/currdenom);i++){
vals[ind] = i;
printAllCents(ind+1,denom,N-i*currdenom,vals);
}
}
The sub problem is a typical Dynamic Programming problem.
/* Q: Given some dollar value in cents (e.g. 200 = 2 dollars, 1000 = 10 dollars),
find the number of combinations of coins that make up the dollar value.
There are only penny, nickel, dime, and quarter.
(quarter = 25 cents, dime = 10 cents, nickel = 5 cents, penny = 1 cent) */
/* A:
Reference: http://andrew.neitsch.ca/publications/m496pres1.nb.pdf
f(n, k): number of ways of making change for n cents, using only the first
k+1 types of coins.
+- 0, n < 0 || k < 0
f(n, k) = |- 1, n == 0
+- f(n, k-1) + f(n-C[k], k), else
*/
#include <iostream>
#include <vector>
using namespace std;
int C[] = {1, 5, 10, 25};
// Recursive: very slow, O(2^n)
int f(int n, int k)
{
if (n < 0 || k < 0)
return 0;
if (n == 0)
return 1;
return f(n, k-1) + f(n-C[k], k);
}
// Non-recursive: fast, but still O(nk)
int f_NonRec(int n, int k)
{
vector<vector<int> > table(n+1, vector<int>(k+1, 1));
for (int i = 0; i <= n; ++i)
{
for (int j = 0; j <= k; ++j)
{
if (i < 0 || j < 0) // Impossible, for illustration purpose
{
table[i][j] = 0;
}
else if (i == 0 || j == 0) // Very Important
{
table[i][j] = 1;
}
else
{
// The recursion. Be careful with the vector boundary
table[i][j] = table[i][j-1] +
(i < C[j] ? 0 : table[i-C[j]][j]);
}
}
}
return table[n][k];
}
int main()
{
cout << f(100, 3) << ", " << f_NonRec(100, 3) << endl;
cout << f(200, 3) << ", " << f_NonRec(200, 3) << endl;
cout << f(1000, 3) << ", " << f_NonRec(1000, 3) << endl;
return 0;
}
I looked into this once a long time ago, and you can read my little write-up on it. Here’s the Mathematica source.
By using generating functions, you can get a closed-form constant-time solution to the problem. Graham, Knuth, and Patashnik’s Concrete Mathematics is the book for this, and contains a fairly extensive discussion of the problem. Essentially you define a polynomial where the nth coefficient is the number of ways of making change for n dollars.
Pages 4-5 of the writeup show how you can use Mathematica (or any other convenient computer algebra system) to compute the answer for 10^10^6 dollars in a couple seconds in three lines of code.
(And this was long enough ago that that’s a couple of seconds on a 75Mhz Pentium...)
Both: iterate through all denominations from high to low, take one of denomination, subtract from requried total, then recurse on remainder (constraining avilable denominations to be equal or lower to current iteration value.)
Duh, I feel stupid right now. Below there is an overly complicated solution, which I'll preserve because it is a solution, after all. A simple solution would be this:
// Generate a pretty string
val coinNames = List(("quarter", "quarters"),
("dime", "dimes"),
("nickel", "nickels"),
("penny", "pennies"))
def coinsString =
Function.tupled((quarters: Int, dimes: Int, nickels:Int, pennies: Int) => (
List(quarters, dimes, nickels, pennies)
zip coinNames // join with names
map (t => (if (t._1 != 1) (t._1, t._2._2) else (t._1, t._2._1))) // correct for number
map (t => t._1 + " " + t._2) // qty name
mkString " "
))
def allCombinations(amount: Int) =
(for{quarters <- 0 to (amount / 25)
dimes <- 0 to ((amount - 25*quarters) / 10)
nickels <- 0 to ((amount - 25*quarters - 10*dimes) / 5)
} yield (quarters, dimes, nickels, amount - 25*quarters - 10*dimes - 5*nickels)
) map coinsString mkString "\n"
Here is the other solution. This solution is based on the observation that each coin is a multiple of the others, so they can be represented in terms of them.
// Just to make things a bit more readable, as these routines will access
// arrays a lot
val coinValues = List(25, 10, 5, 1)
val coinNames = List(("quarter", "quarters"),
("dime", "dimes"),
("nickel", "nickels"),
("penny", "pennies"))
val List(quarter, dime, nickel, penny) = coinValues.indices.toList
// Find the combination that uses the least amount of coins
def leastCoins(amount: Int): Array[Int] =
((List(amount) /: coinValues) {(list, coinValue) =>
val currentAmount = list.head
val numberOfCoins = currentAmount / coinValue
val remainingAmount = currentAmount % coinValue
remainingAmount :: numberOfCoins :: list.tail
}).tail.reverse.toArray
// Helper function. Adjust a certain amount of coins by
// adding or subtracting coins of each type; this could
// be made to receive a list of adjustments, but for so
// few types of coins, it's not worth it.
def adjust(base: Array[Int],
quarters: Int,
dimes: Int,
nickels: Int,
pennies: Int): Array[Int] =
Array(base(quarter) + quarters,
base(dime) + dimes,
base(nickel) + nickels,
base(penny) + pennies)
// We decrease the amount of quarters by one this way
def decreaseQuarter(base: Array[Int]): Array[Int] =
adjust(base, -1, +2, +1, 0)
// Dimes are decreased this way
def decreaseDime(base: Array[Int]): Array[Int] =
adjust(base, 0, -1, +2, 0)
// And here is how we decrease Nickels
def decreaseNickel(base: Array[Int]): Array[Int] =
adjust(base, 0, 0, -1, +5)
// This will help us find the proper decrease function
val decrease = Map(quarter -> decreaseQuarter _,
dime -> decreaseDime _,
nickel -> decreaseNickel _)
// Given a base amount of coins of each type, and the type of coin,
// we'll produce a list of coin amounts for each quantity of that particular
// coin type, up to the "base" amount
def coinSpan(base: Array[Int], whichCoin: Int) =
(List(base) /: (0 until base(whichCoin)).toList) { (list, _) =>
decrease(whichCoin)(list.head) :: list
}
// Generate a pretty string
def coinsString(base: Array[Int]) = (
base
zip coinNames // join with names
map (t => (if (t._1 != 1) (t._1, t._2._2) else (t._1, t._2._1))) // correct for number
map (t => t._1 + " " + t._2)
mkString " "
)
// So, get a base amount, compute a list for all quarters variations of that base,
// then, for each combination, compute all variations of dimes, and then repeat
// for all variations of nickels.
def allCombinations(amount: Int) = {
val base = leastCoins(amount)
val allQuarters = coinSpan(base, quarter)
val allDimes = allQuarters flatMap (base => coinSpan(base, dime))
val allNickels = allDimes flatMap (base => coinSpan(base, nickel))
allNickels map coinsString mkString "\n"
}
So, for 37 coins, for example:
scala> println(allCombinations(37))
0 quarter 0 dimes 0 nickels 37 pennies
0 quarter 0 dimes 1 nickel 32 pennies
0 quarter 0 dimes 2 nickels 27 pennies
0 quarter 0 dimes 3 nickels 22 pennies
0 quarter 0 dimes 4 nickels 17 pennies
0 quarter 0 dimes 5 nickels 12 pennies
0 quarter 0 dimes 6 nickels 7 pennies
0 quarter 0 dimes 7 nickels 2 pennies
0 quarter 1 dime 0 nickels 27 pennies
0 quarter 1 dime 1 nickel 22 pennies
0 quarter 1 dime 2 nickels 17 pennies
0 quarter 1 dime 3 nickels 12 pennies
0 quarter 1 dime 4 nickels 7 pennies
0 quarter 1 dime 5 nickels 2 pennies
0 quarter 2 dimes 0 nickels 17 pennies
0 quarter 2 dimes 1 nickel 12 pennies
0 quarter 2 dimes 2 nickels 7 pennies
0 quarter 2 dimes 3 nickels 2 pennies
0 quarter 3 dimes 0 nickels 7 pennies
0 quarter 3 dimes 1 nickel 2 pennies
1 quarter 0 dimes 0 nickels 12 pennies
1 quarter 0 dimes 1 nickel 7 pennies
1 quarter 0 dimes 2 nickels 2 pennies
1 quarter 1 dime 0 nickels 2 pennies
This is the improvement of Zihan's answer. The great deal of unnecessary loops comes when the denomination is just 1 cent.
It's intuitive and non-recursive.
public static int Ways2PayNCents(int n)
{
int numberOfWays=0;
int cent, nickel, dime, quarter;
for (quarter = 0; quarter <= n/25; quarter++)
{
for (dime = 0; dime <= n/10; dime++)
{
for (nickel = 0; nickel <= n/5; nickel++)
{
cent = n - (quarter * 25 + dime * 10 + nickel * 5);
if (cent >= 0)
{
numberOfWays += 1;
Console.WriteLine("{0},{1},{2},{3}", quarter, dime, nickel, cent);
}
}
}
}
return numberOfWays;
}
Below is a python program to find all combinations of money. This is a dynamic programming solution with order(n) time. Money is 1,5,10,25
We traverse from row money 1 to row money 25 (4 rows). Row money 1 contains the count if we only consider money 1 in calculating the number of combinations. Row money 5 produces each column by taking the count in row money r for the same final money plus the previous 5 count in its own row (current position minus 5). Row money 10 uses row money 5, which contains counts for both 1,5 and adds in the previous 10 count (current position minus 10). Row money 25 uses row money 10, which contains counts for row money 1,5,10 plus the previous 25 count.
For example, numbers[1][12] = numbers[0][12] + numbers[1][7] (7 = 12-5) which results in 3 = 1 + 2; numbers[3][12] = numbers[2][12] + numbers[3][9] (-13 = 12-25) which results in 4 = 0 + 4, since -13 is less than 0.
def cntMoney(num):
mSz = len(money)
numbers = [[0]*(1+num) for _ in range(mSz)]
for mI in range(mSz): numbers[mI][0] = 1
for mI,m in enumerate(money):
for i in range(1,num+1):
numbers[mI][i] = numbers[mI][i-m] if i >= m else 0
if mI != 0: numbers[mI][i] += numbers[mI-1][i]
print('m,numbers',m,numbers[mI])
return numbers[mSz-1][num]
money = [1,5,10,25]
num = 12
print('money,combinations',num,cntMoney(num))
output:
('m,numbers', 1, [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1])
('m,numbers', 5, [1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 3, 3, 3])
('m,numbers', 10, [1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 4, 4, 4])
('m,numbers', 25, [1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 4, 4, 4])
('money,combinations', 12, 4)
Below is python solution:
x = []
dic = {}
def f(n,r):
[a,b,c,d] = r
if not dic.has_key((n,a,b,c,d)): dic[(n,a,b,c,d)] = 1
if n>=25:
if not dic.has_key((n-25,a+1,b,c,d)):f(n-25,[a+1,b,c,d])
if not dic.has_key((n-10,a,b+1,c,d)):f(n-10,[a,b+1,c,d])
if not dic.has_key((n-5,a,b,c+1,d)):f(n-5,[a,b,c+1,d])
if not dic.has_key((n-1,a,b,c,d+1)):f(n-1,[a,b,c,d+1])
elif n>=10:
if not dic.has_key((n-10,a,b+1,c,d)):f(n-10,[a,b+1,c,d])
if not dic.has_key((n-5,a,b,c+1,d)):f(n-5,[a,b,c+1,d])
if not dic.has_key((n-1,a,b,c,d+1)):f(n-1,[a,b,c,d+1])
elif n>=5:
if not dic.has_key((n-5,a,b,c+1,d)):f(n-5,[a,b,c+1,d])
if not dic.has_key((n-1,a,b,c,d+1)):f(n-1,[a,b,c,d+1])
elif n>=1:
if not dic.has_key((n-1,a,b,c,d+1)):f(n-1,[a,b,c,d+1])
else:
if r not in x:
x.extend([r])
f(100, [0,0,0,0])
print x
PHP Code to breakdown an amount into denominations:
//Define the denominations
private $denominations = array(1000, 500, 200, 100, 50, 40, 20, 10, 5, 1);
/**
* S# countDenomination() function
*
* @author Edwin Mugendi <[email protected]>
*
* Count denomination
*
* @param float $original_amount Original amount
*
* @return array with denomination and count
*/
public function countDenomination($original_amount) {
$amount = $original_amount;
$denomination_count_array = array();
foreach ($this->denominations as $single_denomination) {
$count = floor($amount / $single_denomination);
$denomination_count_array[$single_denomination] = $count;
$amount = fmod($amount, $single_denomination);
}//E# foreach statement
var_dump($denomination_count_array);
return $denomination_count_array;
//return $denomination_count_array;
}
//E# countDenomination() function
This is my answer in Python. It does not use recursion:
def crossprod (list1, list2):
output = 0
for i in range(0,len(list1)):
output += list1[i]*list2[i]
return output
def breakit(target, coins):
coinslimit = [(target / coins[i]) for i in range(0,len(coins))]
count = 0
temp = []
for i in range(0,len(coins)):
temp.append([j for j in range(0,coinslimit[i]+1)])
r=[[]]
for x in temp:
t = []
for y in x:
for i in r:
t.append(i+[y])
r = t
for targets in r:
if crossprod(targets, coins) == target:
print targets
count +=1
return count
if __name__ == "__main__":
coins = [25,10,5,1]
target = 78
print breakit(target, coins)
Example output
...
1 ( 10 cents) 2 ( 5 cents) 58 ( 1 cents)
4 ( 5 cents) 58 ( 1 cents)
1 ( 10 cents) 1 ( 5 cents) 63 ( 1 cents)
3 ( 5 cents) 63 ( 1 cents)
1 ( 10 cents) 68 ( 1 cents)
2 ( 5 cents) 68 ( 1 cents)
1 ( 5 cents) 73 ( 1 cents)
78 ( 1 cents)
Number of solutions = 121
If the currency system allows it, a simple greedy algorithm that takes as many of each coin as possible, starting with the highest value currency.
Otherwise, dynamic programming is required to find an optimal solution quickly since this problem is essentially the knapsack problem.
For example, if a currency system has the coins: {13, 8, 1}, the greedy solution would make change for 24 as {13, 8, 1, 1, 1}, but the true optimal solution is {8, 8, 8}
Edit: I thought we were making change optimally, not listing all the ways to make change for a dollar. My recent interview asked how to make change so I jumped ahead before finishing to read the question.
public static int calcCoins(int cents){
return coins(cents,new int[cents+1]);
}
public static int coins(int cents,int[] memo){
if(memo[cents] != 0){
return -1;
}
int sum = 0;
int arr[] = {25,10,5,1};
for (int i = 0; i < arr.length; i++) {
if(cents/arr[i] != 0){
int temp = coins(cents-arr[i],memo);
if(temp == 0){
sum+=1;
} else if(temp == -1){
sum +=0;
}
else{
sum += temp;
}
}
}
memo[cents] = sum;
return sum;
}
semi-hack to get around the unique combination problem - force descending order:
$denoms = [1,5,10,25]
def all_combs(sum,last)
return 1 if sum == 0
return $denoms.select{|d| d &le sum && d &le last}.inject(0) {|total,denom|
total+all_combs(sum-denom,denom)}
end
This will run slow since it won't be memoized, but you get the idea.
Source: Stackoverflow.com