What Is Greedy Algorithm?

A Greedy Algorithm is a strategy that picks the best solution at every stage without considering what might happen. The greedy algorithm is an algorithmic strategy that makes the best choice at each step, leading to a globally optimum solution. It means that the algorithm picks the best solution at the moment without regard for consequences. It determines the best immediate output but does not consider the big picture. Hence it is considered greedy. In other words, it's like when you order a burger and fries: you might regret eating them later if you're trying to lose weight, but in that moment of deliciousness, it's hard to think about anything else! Greedy algorithms are like that guy who takes the best possible option in every situation and then moves on to the next. They could be better at long-term planning because they try to get the best short-term results without considering how those decisions might impact the whole system. And as we all know, a greedy algorithm can end up with a terrible outcome—like if you try to optimize each part of your body by working for only one muscle group at a time instead of doing full-body workouts. The greedy algorithm is an optimization method that finds the best solution by looking at each possible solution one at a time and choosing the one that seems best. It's like taking a bunch of shortcuts in a manufacturing business: in the short term, large amounts are saved in manufacturing costs, but this eventually leads to downfall since quality is compromised, resulting in product returns and low sales as customers become acquainted with the "cheap" product. But this is only sometimes the case there are many applications where the greedy algorithm works best to find or approximate the globally optimum solution, such as constructing a Huffman tree or a decision-learning tree.