A greedy algorithm builds up a solution by choosing the option that looks the best at every step.
Say you're a cashier and need to give someone 67 cents (US) using as few coins as possible. How would you do it?
Whenever picking which coin to use, you'd take the highest-value coin you could. A quarter, another quarter, then a dime, a nickel, and finally two pennies. That's a greedy algorithm, because you're always greedily choosing the coin that covers the biggest portion of the remaining amount.
Some other places where a greedy algorithm gets you the best solution:
- Trying to fit as many overlapping meetings as possible in a conference room? At each step, schedule the meeting that ends earliest.
- Looking for a minimum spanning tree in a graph? At each step, greedily pick the cheapest edge that reaches a new vertex.
Careful: sometimes a greedy algorithm doesn't give you an optimal solution:
- When filling a duffel bag with cakes of different weights and values, choosing the cake with the highest value per pound doesn't always produce the best haul.
- To find the cheapest route visiting a set of cities, choosing to visit the cheapest city you haven't been to yet doesn't produce the cheapest overall itinerary.
Validating that a greedy strategy always gets the best answer is tricky. Either prove that the answer produced by the greedy algorithm is as good as an optimal answer, or run through a rigorous set of test cases to convince your interviewer (and yourself) that it's correct.