Lecturer: Vadim Lozin
Term(s): Term 2
Status for Mathematics students: List A for mathematics
Commitment: 30 lectures.
Assessment: 2 hour exam
Prerequisites: No formal prerequisites. Students who have taken CS126 Design of Information Structures, CS137 Discrete Mathematics and its Applications 2, MA241 Combinatorics or CS260 Algorithms will find it helpful, but no background from these modules will be assumed.
Content: The focus of combinatorial optimisation is on finding the "optimal" object (i.e. an object that maximises or minimises a particular function) from a finite set of mathematical objects. Problems of this type arise frequently in real world settings and throughout pure and applied mathematics, operations research and theoretical computer science. Typically, it is impractical to apply an exhaustive search as the number of possible solutions grows rapidly with the "size" of the input to the problem. The aim of combinatorial optimisation is to find more clever methods (i.e. algorithms) for exploring the solution space.
This module provides an introduction to combinatorial optimisation. Our main focus is on several fundamental problems arising in graph theory and algorithms developed to solve them. These include problems related to shortest paths, minimum weight spanning trees, matchings, network flows, cliques, colourings and matroids. We will also discuss "intractible" (e.g. NP-hard) problems.
- B. Korte and J. Vygen, Combinatorial Optimization: Theory and Algorithms, Springer, 6th Edition, 2018. E-book available through the Warwick Library; click the link.
- A. Bondy and U. S. R. Murty, Graph Theory with Applications, Elsevier, 1976. Available through the link.
- W.J. Cook, William H. Cunningham, W. R. Pulleybank, and A. Schrijver, Combinatorial Optimization, Wiley-Interscience Series in Discrete Mathematics, 1998.
- C.H. Papadimitriou and K. Steiglitz Combinatorial Optimization: Algorithms and Complexity Optimization: Algorithms and Complexity, Dover Publications, 1998.