# What is a greedy algorithm

## Greedy algorithm

You don't know what **Greedy algorithms** are and what they are, for example, with **shortest routes** have to do? Then you are exactly right here!

- Greedy algorithm definitionin the text
- Example of a greedy procedurein the text

### Greedy algorithm definition

**Greedy algorithms** often find **fast** a **solution**, while other algorithms cannot deliver a result in a finite time.

Often, however, it is the solution found by a greedy algorithm **Not** to the **optimal solution** for the problem. This is due to the way these algorithms work. It will always be that **currently the best decision** made regardless of previous choices or the effects of this choice.

To the greedy, so to the **greedy algorithms**, for example, count the **Algorithm of Prim**, the **Kruskal's algorithm** and the **Dijkstra's algorithm**.

### Example of a greedy procedure

Let's take a closer look at a small one **example** at. You are presented with the following graph:

Your job is that **cheapest way** of **Node A****to F** to find.

How do you proceed? Clear! You realize it **2 ways** there and choose the one who, in total, the **lowest cost** Has. So it is possible for you with **Cost of 75 from A to F** to get. But what would a **simple greedy algorithm** to do?

Let's start at **Node A**. The task of the greedy algorithm is now that of the **cheapest partial solution** to choose. So he sees that the **Way from A to B** for something **better** is than that from A to C and thus defines that this is the preferred route.

Since it is now **no further options** there is more, so becomes a way with **Total cost of 351** the way with **Cost of 75** preferred just because of **very first step cheaper** is. This is a good way of seeing why greedy algorithms are so common **not the optimal solution** deliver.

Then why should you use it? Imagine there were not just two but one very **large number of possibilities**.

A greedy algorithm just has to go through the graph and **always the cheapest option** while a normal algorithm would have to test every single possibility. Since this is often not possible in a finite time, these are greedy algorithms **essential** for many problems.

Great, you know what now **Greedy algorithms** and what they are used for. You also learned why she was a **fast, but not necessarily optimal solution** deliver.

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