• Knowledge of important network algorithms
• Knowledge of important algorithmic techniques and concepts
• Ability to model problems from applications as an (algorithmic) network problem
• Ability to apply algorithmic techniques, to solve algorithmic network problems
• Ability to prove correctness of a network algorithm
• Ability to formulate graph and network algorithms
• Ability to analyze the running time of network algorithms

Assessment
There are a number (7 to 8) exercise sets, and two exams.
In order to pass the course, you need:

• an average grade of at least 5.5 (computation of the average is explained at the course website).
• at least an average grade of 6.0 on the exercises.
• an average of at least 5.0 for the exams.

The exercise sets count for 30 percent of the end note, and the two exams each for 35 percent.

A repair test requires at least a 4 for the original test.

Prerequisites
We expect basic mathematic and algorithmic skills and knowledge.
Besides the basics, we also expect the students to be familiar with the theory of NP-completeness. This is taught in courses such as INFOAL Algorithmiek (bachelor level 3), or  INFOMADS Algorithms for decision support (master).
If you have not taken these courses and want to take the Algorithm and Networks course, please study the chapter (34)  on NP-completeness in "Introduction to Algorithms" (Thomas H. Cormen et al, 3rd edition of the book).

In this course a number of advanced techniques for efficient algorithm design are studied, often at the hand of problems from networks and graphs.
n many applications, networks and graphs are used as a model. Typical examples are networks of roads, or electronic networks. In other applications, the graph model may be less obvious, but appears to be very useful, like for scheduling problems.
In this course, the translation of problem to network model is treated, and algorithmic problems and their solutions on networks and graphs are looked into.
Some topics are: shortest paths, flow, matchings, triangulated graphs, treewidth, graph isomorphism, graph drawing, exact algorithms for fundamental graph problems, small world networks, facility location.

Course form
Lectures.

Literature
Most literature will be handed out during the course