# Greedy Programming explained with real world examples

Greedy algorithms are a class of algorithms that make locally optimal choices at each step, with the hope of finding a global optimum.They are commonly used in data structures such as graphs, trees, and arrays to solve a variety of optimization problems.

### Introduction

Greedy algorithms are based on the principle of making the best possible choice at each step, without considering the consequences of that choice in the future.They are often used for optimisation problems, such as finding the shortest path between two points, minimising the cost of a set of operations, or maximising the profit from a set of investments.

### Understanding Greedy Algorithms

Greedy algorithms are widely used in real-world applications, such as scheduling tasks on a processor, designing networks, and optimising resource allocation in cloud computing.For example, the Dijkstra’s algorithm for finding the shortest path in a graph is a classic example of a greedy algorithm.

### Real-World Examples

Implementing greedy algorithms involves designing a suitable data structure and developing an algorithm that makes locally optimal choices at each step.The choice of data structure depends on the nature of the problem and the efficiency of the algorithm.

### Implementing Greedy Algorithms

At each step of a greedy algorithm, the algorithm chooses the locally optimal choice without considering the future consequences.The algorithm continues this process until a global optimum is reached or the problem is solved.

### How Greedy Algorithms Work

Greedy algorithms are often simple and easy to implementThey can also be efficient and provide quick solutions to many optimization problems..