Greedy vs. Dynamic Programming
Greedy vs. Dynamic Programming: A Comprehensive Guide When faced with optimization problems, two fundamental strategies to consider are Greedy Algorithms and Dynamic Programming (DP) . Both aim to solve problems efficiently, but their techniques, problem suitability, memory usage, and optimality differ significantly. This guide delves deep into both concepts, compares their strengths and limitations, and applies them to the Knapsack Problem . What is a Greedy Algorithm? A Greedy Algorithm builds a solution by making a series of local optimal decisions , assuming these will result in a globally optimal solution . It is based on the premise that picking the best option at each step will lead to the overall best outcome. However, greedy algorithms do not backtrack or revise their decisions, which can sometimes result in suboptimal solutions. These algorithms are often used for optimization problems , such as finding the shortest...