## Is coin change possible problem?

Therefore, the problem has optimal substructure property as the problem can be solved using solutions to subproblems. Following is a simple recursive implementation of the Coin Change problem.

**What is coin change algorithm?**

Introduction to Coin Change Problem You are given an array of coins with varying denominations and an integer sum representing the total amount of money; you must return the fewest coins required to make up that sum; if that sum cannot be constructed, return -1.

**Is coin change knapsack problem?**

Coin change problem is very similar to unbounded knapsack problem which can be solved easily and efficiently by using Dynamic Programming. General task is to find maximum number of ways to add the coins from the array for given amount.

### What is coin row problem?

Coin-row problem: There is a row of n coins whose values are some positive integers C0, C2, . . . , Cn-1, not necessarily distinct. The goal is to pick up the maximum amount of money subject to the constraint that no two coins adjacent in the initial row can be picked up.

**Is coin change greedy?**

The famous coin change problem is a classic example of using greedy algorithms. Let’s understand what the problem is. According to the coin change problem, we are given a set of coins of various denominations. Consider the below array as the set of coins where each element is basically a denomination.

**What is time complexity of the coin row problem?**

The time complexity of the coin change problem is (in any case) (n*c), and the space complexity is (n*c) (n).

## Is coin change a knapsack problem?

The coin-change problem resembles the 0-1 Knapsack Problem in Dynamic Programming. It has two versions: Finding the minimum number of coins, of certain denominations, required to make a given sum. Finding the total number of possible ways a given sum can be made from a given set of coins.

**What is change making problem greedy algorithm?**

A Greedy algorithm is one of the problem-solving methods which takes optimal solution in each step. The Greedy algorithm attempts to take the best in each step and it doesn’t care about the overall result. Greedy Approach – “Living in the present. Don’t overthink about the future”.