Dynamic Programing
Table of Contents
Dynamic programming is an algorithmic technique for solving problems by breaking them down into smaller subproblems and storing the solutions to these subproblems in order to avoid recomputing them. It is a powerful technique that is widely used in computer science, and can be applied to a wide range of problems, including optimization problems, search problems, and decision-making problems.
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One common application of dynamic programming is in graph algorithms. Many graph problems can be solved using dynamic programming, as the structure of a graph often lends itself to a recursive, divide-and-conquer approach.
One popular dynamic programming algorithm for graphs is the Floyd-Warshall algorithm, which is used to find the shortest path between all pairs of vertices in a weighted graph. The algorithm works by iterating over the vertices of the graph and using a recursive formula to compute the shortest path between each pair of vertices.
Another popular dynamic programming algorithm for graphs is the Bellman-Ford algorithm, which is used to find the shortest path from a single source vertex to all other vertices in a weighted graph. The algorithm works by iterating over the edges of the graph and using a recursive formula to update the shortest path to each vertex.
Dynamic programming can also be used to solve optimization problems on graphs. For example, the Knapsack problem is a classic optimization problem in which a thief has a knapsack with a certain weight capacity, and must choose which items to steal in order to maximize the value of the stolen goods. This problem can be solved using dynamic programming by breaking it down into smaller subproblems and storing the solutions to these subproblems in a table.
Overall, dynamic programming is a powerful technique for solving a wide range of problems, including many graph problems. By breaking down a problem into smaller subproblems and storing the solutions to these subproblems, you can avoid recomputing them and achieve significant improvements in
# Conclusion
That its folks! Thank you for following up until here, and if you have any question or just want to chat, send me a message on GitHub of this project or an email. Am I doing it right? Was it a good hello world post for the blogging community?
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# Conclusion
That its folks! Thank you for following up until here, and if you have any question or just want to chat, send me a message on GitHub of this project or an email. Am I doing it right?
https://github.com/lbenicio.github.io