Advanced Algorithms | Network Optimization | Linear Programming

Dive deeper into advanced algorithmic techniques and their applications in network analysis, optimization, and theoretical computer science.

Introduction

This course covers advanced algorithms and techniques for network optimization, linear programming, and approximation algorithms. It provides a deeper exploration of topics beyond the introductory algorithms course.

Highlights

• Algorithms for network optimization, including maximum flow, minimum-cost flow, matching, assignment, and minimum cut problems
• Introduction to linear programming and use of LP duality for algorithm design and analysis
• Approximation algorithms for NP-complete problems such as Steiner Trees, Traveling Salesman, and scheduling problems
• Coverage of randomized algorithms and introduction to online algorithms

Recommendation

This course is recommended for students who have already taken an introductory algorithms course and want to dive deeper into advanced algorithmic techniques and their applications. It is particularly useful for those interested in optimization, network analysis, and theoretical computer science.