A greedy algorithm follows the problem-solving heuristic of making the locally optimal choice (the best solution at the time) at each stage with the hope of finding a global optimum (global best solution). It does not evaluate the bigger picture like a dynamic programming algorithm does.
Let's take a look at how we can solve the min-coin change and knapsack problems we covered in the dynamic programming topic using the greedy approach.
Note
We covered some other greedy algorithms in this book in Chapter 12, Graphs, such as Dijkstra's algorithm, Prim's algorithm, and Kruskal's algorithm.
The min-coin change problem can also be resolved with a greedy algorithm. Most of the time, the result is also optimal, but for some denominations, the result will not be optimal.
Let's take a look at the algorithm:
function minCoinChange(coins, amount) {
const change = [];
let total = 0;
for (let i = coins.length; i >= 0; i--) { // {1}
const coin = coins...