What are the differences between various algorithmic strategies?

What are the differences between various algorithmic strategies?

There are several algorithmic strategies, including greedy algorithms, dynamic programming, and divide-and-conquer. Each has its strengths and weaknesses depending on the problem.

Can you explain greedy algorithms in more detail?

Greedy algorithms make the locally optimal choice at each stage with the hope of finding a global optimum. They are often used in optimization problems.

What about dynamic programming? How is it different?

Dynamic programming solves problems by breaking them down into simpler subproblems and storing the results to avoid redundant calculations. It's particularly useful for problems with overlapping subproblems.

Can you give an example of a problem suited for divide-and-conquer?

Sure! A classic example is the Merge Sort algorithm, which divides the array into halves, sorts each half, and then merges them back together.