Introduction
In the previous chapter, we discussed the divide-and-conquer algorithm design technique, which solves a given problem by dividing the input into smaller subproblems, solving each subproblem, and subsequently merging the results. Continuing our theme of algorithm design paradigms, we will now look at our next topic: the greedy approach.
On each iteration, a greedy algorithm is one that picks the 'seemingly best' alternative. In other words, a greedy solution to a problem composes a globally optimal solution to the given problem from a series of locally optimal solutions. For example, the following screenshot shows the shortest path that a car can take from Dulles International Airport in Washington DC to an office building in East Riverdale. Naturally, the path shown is also the shortest for any two points on the path that are not the starting and ending points:
