Objectives of Programme's Learning Outcomes

• Have integrated and elaborate mathematical knowledge.
• Mobilise the Bachelor's course in mathematics to address complex issues and have profound mathematical expertise to complement the knowledge developed in the Bachelor's course.
• Research mathematical literature in an efficient and relevant way.
• Apply innovative methods to solve an unprecedented problem in mathematics or within its applications.
• Mobilise knowledge, and research and analyse various information sources to propose innovative solutions targeted unprecedented issues.
• Appropriately make use of computer tools, as required by developing a small programme.
• Communicate clearly.
• Communicate the results of mathematical or related fields, both orally and in writing, by adapting to the public.

Learning Outcomes of UE

Understand the fundamental notions and problems appearing in graph theory;study the corresponding algorithms;go deeply into algorithmic notions from the algorithm efficiency point of view;understand the fundamental problems and techniques of combinatorial optimization;illustrate some methods on some particular problems;show the utility of algorithms for solving practical problems in scheduling management, logistics,...

Content of UE

Basic notions of graph theory and data structure; study of classical graph theory problems : trees, shortest paths, connexity, flows;introduction to complexity theory : P and NP classes; study of classical combinatorial optimization problems : knapsack, set covering, travelling salesman; introduction to metaheuristics.

The teaching methods are likely to be adjusted according to the educational context
imposed by the health measures.
 

Prior Experience

Linear programming; duality; notion of algorithm.

Type of Assessment for UE in Q1

• Presentation and/or works
• Written examination

Q1 UE Assessment Comments

Report of project/challenge: 20%.   Written examination covering both parts of the course: Graph theory  : (theory and exercises)  40% Combinatorial optimization : (theory and exercises)  40%

The evaluation procedures are likely to be adjusted according to
the educational/assessment context imposed by health measures.

Type of Assessment for UE in Q3

• Presentation and/or works
• Written examination

Q3 UE Assessment Comments

Report of project/challenge  : 20%.   Written examination covering both parts of the course: Graph theory  : (theory and exercises)  40% Combinatorial optimization : (theory and exercises)  40%

The evaluation procedures are likely to be adjusted according to
the educational/assessment context imposed by health measures.

 

Type of Resit Assessment for UE in Q1 (BAB1)

• N/A

Q1 UE Resit Assessment Comments (BAB1)

Not applicable