7 Greedy Algorithms Interview Questions (ANSWERED) Software Devs Must Know

We call algorithms greedy when they utilise the greedy property. The greedy property is:

At that exact moment in time, what is the optimal choice to make?

Greedy algorithms are greedy. They do not look into the future to decide the global optimal solution. They are only concerned with the optimal solution locally. This means that the overall optimal solution may differ from the solution the greedy algorithm chooses.

They never look backwards at what they've done to see if they could optimise globally. This is the main difference between Greedy Algorithms and Dynamic Programming.

Greedy algorithms are quick. A lot faster than the two other alternatives (Divide & Conquer, and Dynamic Programming). They're used because they're fast. Sometimes, Greedy algorithms give the global optimal solution every time. Some of these algorithms are:

• Dijkstra's Algorithm
• Kruskal's algorithm
• Prim's algorithm
• Huffman trees

These algorithms are Greedy, and their Greedy solution gives the optimal solution.

• The choice made by a greedy algorithm may depend on choices made so far but not on future choices or all the solutions to the subproblem. It iteratively makes one greedy choice after another, reducing each given problem into a smaller one. In other words, a greedy algorithm never reconsiders its choices.

• This is the main difference from dynamic programming, which is exhaustive and is guaranteed to find the solution. After every stage, dynamic programming makes decisions based on all the decisions made in the previous stage, and may reconsider the previous stage's algorithmic path to solution.

For example, let's say that you have to get from point A to point B as fast as possible, in a given city, during rush hour. A dynamic programming algorithm will look into the entire traffic report, looking into all possible combinations of roads you might take, and will only then tell you which way is the fastest. Of course, you might have to wait for a while until the algorithm finishes, and only then can you start driving. The path you will take will be the fastest one (assuming that nothing changed in the external environment).

On the other hand, a greedy algorithm will start you driving immediately and will pick the road that looks the fastest at every intersection. As you can imagine, this strategy might not lead to the fastest arrival time, since you might take some "easy" streets and then find yourself hopelessly stuck in a traffic jam.