How do backtracking and greedy algorithms differ?

What are the main differences between backtracking and greedy algorithms?

Backtracking is a systematic way of trying out different solutions until a valid one is found, while greedy algorithms make the locally optimal choice at each step with the hope of finding a global optimum.

Can you give an example of a problem suited for backtracking?

Sure! The N-Queens problem is a classic example where backtracking is used to place queens on a chessboard without threatening each other.

And what about a problem that works well with greedy algorithms?

A good example is the Coin Change problem, where you want to make change for a certain amount using the least number of coins.

Are there situations where one is better than the other?

Yes, backtracking is often better for problems with many constraints, while greedy algorithms are more efficient for optimization problems where local choices lead to a global solution.