Kotlin coding test course, greedy algorithm

In this course, we will learn about greedy algorithms using Kotlin, and solve problems that often appear in actual coding tests. A greedy algorithm is a method that finds an overall optimal solution by making the best choice at the moment. This algorithm has properties of optimal substructure and greedy choice. We will delve into the concept of greedy algorithms with specific examples.

1. Understanding Greedy Algorithms

A greedy algorithm is a method that derives the final answer by repeatedly making the ‘best choice at the moment’ to solve a problem. This algorithm might appear simple, but it does not guarantee an optimal solution for all problems. However, for specific problems, using a greedy algorithm can lead to efficient solutions.

1.1 Characteristics of Greedy Algorithms

  • Optimal Substructure: The optimal solution of the problem consists of the optimal solutions of its subproblems.
  • Greedy Choice Property: The choice that seems best at the present is continuously repeated to find the optimal solution.

2. Examples of Problems Using Greedy Algorithms

The problem we will solve this time is the ‘Coin Change Problem’. This problem is a typical example that can be easily solved using greedy algorithms.

Problem: Coin Change

You want to give back the change after purchasing items in a store using the minimum number of coins. The types of coins available and their respective values are as follows.

  • 500 won, 100 won, 50 won, 10 won

For example, if the amount to be given back is 760 won, the change should be given as follows:

  • 500 won: 1 coin
  • 100 won: 2 coins
  • 50 won: 1 coin
  • 10 won: 1 coin

Implement a program that calculates the minimum number of coins required to give the change.

3. Problem Analysis

The reason we approach this problem with a greedy algorithm is that the values of the coins differ. We can use a method that starts with the coin of the highest value and uses it as much as possible to calculate the remaining amount. This allows us to provide the change using the minimum number of coins.

3.1 Algorithm Explanation

We can solve the problem through the following steps:

  1. Input the amount of change to be received.
  2. Starting from the highest value coins, select as many coins as possible.
  3. Repeat this process until the remaining amount is 0.
  4. Output the number of coins used.

4. Kotlin Implementation

Below is an example of implementing the above algorithm in Kotlin.


fun main() {
    // Sort the types of coins in descending order.
    val coins = arrayOf(500, 100, 50, 10)
    // Receive change from user
    val amount = 760 // Set to 760 won as an example.
    
    var remaining = amount
    var coinCount = 0

    for (coin in coins) {
        // Use current coins as much as possible.
        coinCount += remaining / coin
        remaining %= coin
        if (remaining == 0) break
    }

    println("Minimum number of coins to give back: $coinCount")
}

4.1 Code Explanation

The code above works as follows:

  • The values of the coins are stored in an array and sorted in descending order.
  • The user inputs the required change.
  • For each coin value, the maximum number is calculated and the remaining amount is updated.
  • Finally, the number of coins used is output.

5. Example Execution and Result

When the above code is executed, you can see the following result:


Minimum number of coins to give back: 5

This result indicates that 1 coin of 500 won, 2 coins of 100 won, 1 coin of 50 won, and 1 coin of 10 won were used, totaling 5 coins. This is the result using the minimum number of coins.

6. Additional Problems and Applications

Based on the content of this course, try solving the following modified problems:

  • If the types of coins are given randomly, how can you still find the minimum number of coins?
  • What algorithm will you use if the values of the coins are given in ascending order?

7. Conclusion

We learned that greedy algorithms are a powerful tool for efficient problem-solving. We experienced the implementation of greedy algorithms through the coin change problem and hope to increase our understanding through various application problems.

Additionally, I hope you practice solving more problems to fully master greedy algorithms. Thank you!