## MA413E - Combinatorial optimization

### Objectives

#### General objective:

Upon completion of this course the student will be able to:

- identify an optimization problem in a real-world context,

- formulate some simple continuous or combinatorial optimization problems in an appropriate modeling framework

- describe and apply manually a set of basic mathematical and graph optimization algorithms

- choose and apply an appropriate algorithm to solve basic optimization problems

#### Detailed objectives:

Upon completion of this course the student will be able to:

- identify and differentiate continuous and combinatorial optimization problems as well as linear and non-linear optimization problems,

- describe and model basic problems of graph theory : minimum weight spanning tree problem, shortest path problem, project scheduling problem, maximum flow problem,

- build linear/ non-linear mathematical optimization models

- describe and apply manually the following concepts and algorithms:

- optimality conditions,

- gradient methods,

- projected gradient methods,

- penalty methods,

- Simplex algorithm,

- branch and bound search,

- basic algorithms of graph theory : Prim, Kruskal, Dijkstra, Bellman and Ford-Fulkerson

### In brief

ECTS credits : cf Teaching Unit

### Contact(s)

#### Andrija VIDOSAVLJEVIC

Email : andrija.vidosavljevic @ enac.fr

### Places

- Toulouse