|Delivery Type||Delivery length / details|
|Seminars / Tutorials||3 x 1 hour example classes|
|Lecture||19 x 1 hour lectures|
|Assessment Type||Assessment length / details||Proportion|
|Semester Exam||2 Hours (written examination)||100%|
|Supplementary Exam||2 Hours (written examination)||100%|
On completion of this module, students should be able to:
1. investigate elementary properties of graphs;
2. perform simple graph construction;
3. represent abstract graphs diagrammatically;
4. determine whether a graph satisfies various criteria;
5. apply algorithms for finding components;
6. describe the algorithms of Dijkstra and Floyd, and to apply them in simple cases;
7. apply critical path analysis to simple projects;
8. apply either Prim's or Kruskal's algorithm for finding optimum weight spanning trees;
9. apply the Ford-Fulkerson algorithm to a transport network to find a maximum flow.
Graph theory has developed from research into a number of classical problems - Euler's Konigsberg Bridge Problem, Kirchoff's Electrical Network Problem, Cayley's Enumeration of Chemical Graphs and the Four Colour Problem for Plane Maps. A full solution is found to the Euler Problem and a related problem due to Hamilton is studied. Shortest and longest path algorithms are given with applications, for instance, to job scheduling (PERT). Algorithms are described for finding optimum weight spanning trees inweighted graphs. They can be used, for example, to find least cost connected transport networks. The theory of flows in transport networks is outlined: in paticular the max-flow-min-cut theorem. Two areas of application are traffic flows and matching theory.
To provide an introduction to some topics in classical graph theory. To describe network algorithms such as those for finding optimum length paths, optimum weight spanning trees and maximum flows and to illustrate them with applications to simple cases.
2. Paths and components in graphs. Algorithms to determine components. Shortest (Dijkstra) and longest path algorithms. Floyd's algorithm.
3. Topological sorting. Critical Path Analysis.
4. Spanning trees. Prim's and Kruskal's algorithms for finding optimum weight spanning trees.
5. Transport networks. Flows, cuts. The max-flow-min-cut theorem. The Ford-Fulkerson algorithm.
Reading ListRecommended Text
N Biggs (1992) Discrete Mathematics Rev. ed. OUP Primo search R P Grimaldi (1999) Discrete and Combinatorial Mathematics 4th Addison-Wesley Primo search Supplementary Text
C L Liu (1985) Elements of Discrete Mathematics 2nd McGraw-Hill Primo search R J Wilson & J Watkins (1990) Graphs - an Introductory Approach Wiley Primo search
This module is at CQFW Level 6