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Dynamic Programming & Approximation Algorithms for NP-Hard Problems -…
Dynamic Programming & Approximation Algorithms for NP-Hard Problems
Chapter 9: Dynamic Programming
Dynamic Programming:
Introduces the concept of dynamic programming as a problem-solving technique.
Emphasizes the use of optimal substructure and overlapping subproblems.
Three Basic Examples (8.1):
Presents three fundamental examples illustrating the application of dynamic programming.
Demonstrates how breaking down complex problems into overlapping subproblems can lead to efficient solutions.
The Knapsack Problem and Memory Functions (8.2):
Focuses on the application of dynamic programming to the Knapsack Problem.
Introduces the concept of memory functions to optimize the solution space.
Chapter 12: Approximation Algorithms for NP-Hard Problems
Approximation Algorithms for NP-Hard Problems (12.3):
Discusses the use of approximation algorithms for solving NP-hard problems.
Examines strategies to find near-optimal solutions within a reasonable amount of time.
Approximation Algorithms for the Traveling Salesman Problem:
Explores specific approximation algorithms designed for the Traveling Salesman Problem.
Highlights methods to efficiently find close-to-optimal routes.
Approximation Algorithms for the Knapsack Problem:
Examines approximation algorithms tailored for solving the Knapsack Problem.
Illustrates techniques to obtain feasible solutions with a guaranteed level of accuracy.