AMS 303, Graph Theory
Catalog Description: Paths and circuits, trees and tree based algorithms, graph coloring, digraphs, network
flows, matching theory, matroids, and games with graphs.
Prerequisite: AMS 301
Textbooks for Spring 2016:
Coursework found on Amazon (for students who DO use a voucher):
Listed on Amazon as "Applied Combinatorics", by Alan Tucker, 6th edition, published by Pearson; ISBN: 9780558982478; AND
"Introduction to Graph Theory", by Robin Wilson, 6th Edition, John Wiley & Sons; ISBN: 9780273728894
Textbook "Applied Combinatorics" ONLY found on Pearson Publishing Storefront via MyPearsonStore.com (recommended for students who DO NOT use a voucher):
1. Custom and shortened URL: TBA
a. Students can search the custom ISBN on www.MyPearsonStore.com : 9780558982478
3. Go directly to the longer URL: TBA
1. General Graph Theory Foundations ( Wilson, Sect. 2,3,5) – 4 class hours
2. Planar Graphs and Duality ( Wilson, Sect. 12, 13, 15) – 6 class hours
3. Graph Coloring ( Wilson, Sect. 17,19,20) –6 class hours
4. Polya’s Enumeration Formula ( Tucker, Chap 9) – 4 class hours
5. Network Flows ( Tucker, Chap. 4) – 8 class hours
6. Graphs and Games (Tucker, Chap. 11) – 2 class hours
7. Cryptanalysis (Sinkov, Chap. 1,2,3) – 8 class hours
8. Examinations and Review – 4 class hours
Learning Outcomes for AMS 303, Graph Theory
1.) Develop skill with proofs in graph theory (this is the only Applied Math course
that teaches proofs), including:
* the careful use of definitions and stated conditions, and their consequences;
* direct arguments;
* indirect arguments, i.e., proof by contradiction;
* proof with generalized figures.
2.) Examine graph theory topics in greater depth (than AMS 301) with a focus on studying
and extending theoretical results:
* general graph properties;
* planar graphs;
* graph coloring, including edge and face coloring.
3.) Understand the theory behind Polya’s Enumeration Formula and use this understanding in applied problem-solving.
4.) Develop the network algorithms for:
* maximal minimal flows;
* maximal matching;
* the transportation problem.
5.) Understand the set-theoretic constructions underlying the theory of progressively
finite games and apply this knowledge to develop winning strategies for such games:
* kernel of a game;
* level-by-level construction;
* Grundy functions;
* direct sums of games, including Nim.
6.) Use combinatorial reasoning to efficiently solve cryptograms based on keyword transpose encodings; extend this reasoning to solve polyalphabetic codes.