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rting. Linear Programming and Approximation Algorithms Basic LP formulation and duality. Approximation techniques for NP-hard problems, such as the vertex cover and traveling salesman problem. This comprehensive coverage ensures that users can find solutions and insights

y flow algorithms to optimize data routing. Achieved significant reductions in latency and congestion. Case Study 2: Large-Scale Set Cover in Data Mining Implemented greedy approximation algorithms. Manag

the primal-dual approach, which constructs feasible solutions for the primal and dual problems simultaneously. This technique provides approximation guarantees and is particularly useful in network design problems. Randomiz