Dr Tugkan Batu and Prof Andrew Lewis-Pye

This course is available on the MSc in Applicable Mathematics and MSc in Operations Research & Analytics. This course is available as an outside option to students on other programmes where regulations permit.

Students must have completed Algorithms and Computation (MA407) or have taken an equivalent course to provide a basic knowledge in analysis of algorithms: running time and correctness of an algorithm, and basic knowledge of computer programming (preferably in Python). Students should be comfortable with proofs and proof techniques used in pure mathematics.

This course covers modern topics in the theory of algorithms. The topics selected can differ year to year. A syllabus of the course content will be available to students at the beginning of the academic year.

20 hours of lectures and 15 hours of seminars in the WT. 2 hours of lectures in the ST.

Weekly exercises are set and marked. Some of these will include programming exercises in Python.

T. H. Cormen, C. E. Leiserson, R. L. Rivest and C. Stein, Introduction to Algorithms, 3rd or 4th ed., MIT;

M.R. Garey and D.S. Johnson, Computers and Intractability: A Guide to the Theory of NP-completeness, W.H. Freeman, 1979;

D. Williamson, D. B. Shmoys, The Design of Approximation Algorithms, Cambridge University Press, 2011;

V. Vazirani, Approximation Algorithms, 2nd ed., Springer, 2002;

Michael Mitzenmacher and Eli Upfal, Probability and Computing, 1st or 2nd ed., Cambridge University Press.

Exam (65%, duration: 2 hours) in the spring exam period.
Coursework (25%) in the period between WT and ST.
Continuous assessment (10%) in the WT.