Coin change DP solution to keep track of coins

Question

Trying to program a DP solution for the general coin-change problem that also keeps track of which coins are used. So far I have it working to give me the minimum amount of coins needed but can't figure out how to get which coins were used and how many times. I tried setting up another table (boolean) with values if the coin is used but that doesn't seem to work correctly. Any ideas?

public static int minChange(int[] denom, int changeAmount) 
{   
    int m = denom.length;
    int n = changeAmount + 1;

    int[][] table = new int[m][n];
    boolean[][] used = new boolean[m][n];
    for (int j = 0; j < n; j++)
        table[m - 1][j] = j;
    for (int i = 0; i < m; i++)
        table[i][0] = 0;

    for (int i = m-2; i >= 0; i--) //i denotes denominationIndex
    {
        for (int j = 1; j < n; j++) //j denotes current Amount
        {
            if (denom[i] > j)
            {
                table[i][j] = table[i+1][j];
                //used[i][j] = false;
            }
            else
            {
                table[i][j] = Math.min(1 + table[i][j-denom[i]], table[i+1][j]);
                /*Trying table for used coins
                if (1 + table[i][j-denom[i]] < table[i+1][j]) 
                    used[i][j] = true;
                else
                    used[i][j] = false;
                */
            }
        }
    }
}

Answer 1

Solution using Dynamic Programming ::

public int coinchange2(ArrayList<Integer> A, int B) {
    int[] dp = new int[B+1];

    dp[0]=1;

    for(int i=0;i<A.size();i++){
        for(int j=A.get(i);j<=B;j++)
        {
            dp[j]=(dp[j]+dp[j-A.get(i)])%1000007;
        }
    }
    return dp[B];
}

Answer 2

You don't need the first dimension of your dp. You can use an array with only one dimension - the sum of all used coins. Then you can simply store the index of your last used coin for each state of your dp. What I mean is something like:

int[] dp = new int[n];
int[] usedCoin = new int[n];

for (int i=0; i < n; ++i) {
    dp[i] = -1; // state not reached
    usedCoin[i] = -1;
}

dp[0] = 0; // initial state -- we can have sum 0 without any coins
for (int coinId = 0; coinId < m; coinId++)
    for (int sum = 0; sum + denom[coinId] < n; sum++) {
        int newSum = sum + denom[coinId];
        if (dp[newSum] == -1 || dp[newSum] > 1 + dp[sum]) {
            dp[newSum] = 1 + dp[sum];
            usedCoin[newSum] = coinId;
        }
    }

If you want to find a concrete decomposition with minimum amount of coins, you can do something like:

int sum = changeAmount;
System.out.println("The used coins are:");
while (usedCoin[sum] != -1) {
    System.out.print(denom[ usedCoin[sum] ].toString() + " ");
    sum -= denom[ usedCoin[sum] ];
}

Answer 3

public static int minimumNumberOfWays(int []deno, int amount){
    int dp[] = new int[amount+1];
    dp[0]=0;
    int []prevCoin = new int[amount+1];  
    for(int j=1;j<=amount;j++){
        dp[j]=Integer.MAX_VALUE;
        for(int i=0;i<deno.length;i++){
            if(deno[i]<=j && (1+dp[j-deno[i]] < dp[j]) ){               
                dp[j]=1+dp[j-deno[i]];
                prevCoin[j]=deno[i];
            }                   
        }
    }

    int result = dp[amount];
    List<Integer> coinsAdded = new ArrayList<Integer>();
    for(int i=amount;i>=1;){
        coinsAdded.add(prevCoin[i]);
        int j=i;
        i=amount-prevCoin[i];
        amount = amount - prevCoin[j];
    }
    Integer [] coins = coinsAdded.toArray(new Integer[coinsAdded.size()]);
    System.out.println( Arrays.toString(coins)); 

Answer 4

Try this solution, it used only O(M) memory and has O(N*M) complexity:

   public static int[] minChange(int[] denom, int changeAmount)
    {
        int n = denom.length;
        int[] count = new int[changeAmount + 1];
        int[] from = new int[changeAmount + 1];

        count[0] = 1;
        for (int i = 0 ; i < changeAmount; i++)
            if (count[i] > 0)
                for (int j = 0; j < n; j++)
                {
                    int p = i + denom[j];
                    if (p <= changeAmount)
                    {
                        if (count[p] == 0 || count[p] > count[i] + 1)
                        {
                            count[p] = count[i] + 1;
                            from[p] = j;
                        }
                    }
                }

        // No solutions:
        if (count[changeAmount] == 0)
            return null;

        // Build answer.
        int[] result = new int[count[changeAmount] - 1];
        int k = changeAmount;
        while (k > 0)
        {
            result[count[k] - 2] = denom[from[k]];
            k = k - denom[from[k]];
        }

        return result;
    }

Answer 5

Use following pseudo code for reconstructing solution : -

solutionSet = []

i = denom.length-1

j = changeAmount

While(i>=0) {

   if(1+table[i][j-denom[i]]<table[i+1][j]) {
         solutionSet.add(denom[i])
         j = j - denom[i]
     }
   i--
}

Note: There is no need to use extra memory here other than needed to store the solution

Answer 6

public class CoinChange {

    public static void main(String[] args) {
        int[] coins = {1,2,10,5};       
        int amt = 37;       
        makeChange(coins, amt); 
    }

    public static void makeChange(int[] coins, int amount){
        //Sorting the coins
        Arrays.sort(coins);

        int n = coins.length - 1;


        HashMap<Integer, Integer> map = new HashMap<Integer, Integer>();

        while(amount > 0)
        {
            if(coins[n] <= amount)
            {
                int val = 1;
                if(map.containsKey(coins[n]))
                {
                    val = map.get(coins[n]);
                    val = val+1;
                }

                map.put(coins[n], val);

                amount = amount - coins[n];

            }
            else
            {
                n--;
            }

        }

        for(Map.Entry<Integer, Integer> entry: map.entrySet()){

            System.out.println(entry.getKey() +":" + entry.getValue());
        }
    }
}