Greedy algorithms – an introduction

At the beginning of this chapter, we highlighted a key distinction between divide-and-conquer algorithms and dynamic programming: while both strategies leverage optimal substructure, divide-and-conquer algorithms do not typically involve overlapping subproblems. Dynamic programming is particularly effective when overlapping subproblems are present because it avoids redundant calculations by storing and reusing the solutions to these subproblems.

But what happens if we cannot define an optimal substructure for the problem at hand? In such cases, we turn to a different category of algorithms known as Greedy Algorithms. Greedy algorithms adopt a fundamentally different approach to problem-solving. Instead of incrementally building solutions by optimally solving subproblems, as in dynamic programming, a greedy algorithm makes a series of decisions based on what appears to be the best choice at each step, with the expectation that these locally...