CIS 6930: Approximation Algorithms
Announcements   |       Syllabus       |        Schedule        |       Lecture Notes        |     Assignments 
  General Information
  Instructor Information
  • Name: Dr. My T. Thai
  • Office: CSE 566
  • Phone: 352-392-6842
  • Email:
  • Office Hours: W 3:00pm - 4:40pm or by appointments
  Course Description
  • For many optimization problems, it is almost unfeasible to find an exact solution. Since approximation algorithms can provide techniques for near-optimal solutions, the study of this area is significantly important. This course covers several techniques to design and analyze many approximation algorithms for computationally hard problems, divided into three parts: (a) Combinatorial algorithms, (b) Linear programming based algorithms, and (c) Semidefinite programming based algorithms. This course also addresses many other problems existing in the networking research literature.
  Course Objectives
  • Understand the essential techniques to design and analyze approximation algorithms, including the following:
    • Combinatorial methods
    • Linear programming
    • Primal-dual and relaxation methods
    • Semidefinite programming
    • Hardness of approximation
  • Able to model and solve many practical problems raising in our real life applications
  • Grasp the key ideas of graph theory
  • There is no formal prerequisite for this course. However, students should have a solid background in algorithms and the theory of NP-completeness.
  • Required Textbook:
    • Vijay Vazirani, Approximation Algorithms, Springer-Verlag, 2001, ISBN: 3-540-65367-8
  • Recommended Textbooks:
    • Vasek Chvatal, Linear Programming, W. H. Freeman Company, 1st ed., 1983, ISBN: 0716711958
    • Michael R. Garey and David S. Johnson, Computers and Intractability: A Guide to the Theory of NP-Completeness, W. H. Freeman Company, 1990, ISBN: 0716710455
  • Appropriate lecture notes will be provided to cover some topics not covered in the text books
  Grading Policies
  • Homework Assignments:
    • 5 homework assignments, each weighs 10%
    • Due at the beginning of the lecture on the due date
    • No late assignment will be accepted
  • Midterm Exam:
    • One midterm exam,  weighs 20%
    • In class, open books, open notes
  • Final Exam:
    • Weighs 30%
  • Cut-off points:
    • A >= 85%, 85% > B >= 75%, 75% > C >= 65%
  Other Policies
  • Academic Integrity Policy:
  • Collaboration:
    • You may discuss with other students on solutions of homework assignments. However, you must write up solutions on your own independently
    • Cite any sources that you use to help obtain your solutions (but do not copy the sources)
CIS 6930: Approximation Algorithms