Coin changing algorithm - algorithm

Question

Suppose I have a set of coins having denominations a1, a2, ... ak.
One of them is known to be equal to 1.
I want to make change for all integers 1 to n using the minimum number of coins.
Any ideas for the algorithm.
eg. 1, 3, 4 coin denominations
n = 11
optimal selection is 3, 0, 2 in the order of coin denominations.
n = 12
optimal selection is 2, 2, 1.
Note: not homework just a modification of this problem

Answer 1

This is a classic dynamic programming problem (note first that the greedy algorithm does not always work here!).
Assume the coins are ordered so that a_1 > a_2 > ... > a_k = 1. We define a new problem. We say that the (i, j) problem is to find the minimum number of coins making change for j using coins a_i > a_(i + 1) > ... > a_k. The problem we wish to solve is (1, j) for any j with 1 <= j <= n. Say that C(i, j) is the answer to the (i, j) problem.
Now, consider an instance (i, j). We have to decide whether or not we are using one of the a_i coins. If we are not, we are just solving a (i + 1, j) problem and the answer is C(i + 1, j). If we are, we complete the solution by making change for j - a_i. To do this using as few coins as possible, we want to solve the (i, j - a_i) problem. We arrange things so that these two problems are already solved for us and then:
C(i, j) = C(i + 1, j) if a_i > j
= min(C(i + 1, j), 1 + C(i, j - a_i)) if a_i <= j
Now figure out what the initial cases are and how to translate this to the language of your choice and you should be good to go.
If you want to try you hands at another interesting problem that requires dynamic programming, look at Project Euler Problem 67.

Answer 2

Here's a sample implementation of a dynamic programming algorithm in Python. It is simpler than the algorithm that Jason describes, because it only calculates 1 row of the 2D table he describes.
Please note that using this code to cheat on homework will make Zombie Dijkstra cry.
import sys
def get_best_coins(coins, target):
costs = [0]
coins_used = [None]
for i in range(1,target + 1):
if i % 1000 == 0:
print '...',
bestCost = sys.maxint
bestCoin = -1
for coin in coins:
if coin <= i:
cost = 1 + costs[i - coin]
if cost < bestCost:
bestCost = cost
bestCoin = coin
costs.append(bestCost)
coins_used.append(bestCoin)
ret = []
while target > 0:
ret.append(coins_used[target])
target -= coins_used[target]
return ret
coins = [1,10,25]
target = 100033
print get_best_coins(coins, target)

Answer 3

solution in C# code
public static long findPermutations(int n, List<long> c)
{
// The 2-dimension buffer will contain answers to this question:
// "how much permutations is there for an amount of `i` cents, and `j`
// remaining coins?" eg. `buffer[10][2]` will tell us how many permutations
// there are when giving back 10 cents using only the first two coin types
// [ 1, 2 ].
long[][] buffer = new long[n + 1][];
for (var i = 0; i <= n; ++i)
buffer[i] = new long[c.Count + 1];
// For all the cases where we need to give back 0 cents, there's exactly
// 1 permutation: the empty set. Note that buffer[0][0] won't ever be
// needed.
for (var j = 1; j <= c.Count; ++j)
buffer[0][j] = 1;
// We process each case: 1 cent, 2 cent, etc. up to `n` cents, included.
for (int i = 1; i <= n; ++i)
{
// No more coins? No permutation is possible to attain `i` cents.
buffer[i][0] = 0;
// Now we consider the cases when we have J coin types available.
for (int j = 1; j <= c.Count; ++j)
{
// First, we take into account all the known permutations possible
// _without_ using the J-th coin (actually computed at the previous
// loop step).
var value = buffer[i][j - 1];
// Then, we add all the permutations possible by consuming the J-th
// coin itself, if we can.
if (c[j - 1] <= i)
value += buffer[i - c[j - 1]][j];
// We now know the answer for this specific case.
buffer[i][j] = value;
}
}
// Return the bottom-right answer, the one we were looking for in the
// first place.
return buffer[n][c.Count];
}

Answer 4

Following is the bottom up approach of dynamic programming.
int[] dp = new int[amount+ 1];
Array.Fill(dp,amount+1);
dp[0] = 0;
for(int i=1;i<=amount;i++)
{
for(int j=0;j<coins.Length;j++)
{
if(coins[j]<=i) //if the amount is greater than or equal to the current coin
{
//refer the already calculated subproblem dp[i-coins[j]]
dp[i] = Math.Min(dp[i],dp[i-coins[j]]+1);
}
}
}
if(dp[amount]>amount)
return -1;
return dp[amount];
}