MATH-261 / 5 crédits

Langue: Anglais

## Summary

This course is an introduction to linear and discrete optimization. Warning: This is a mathematics course! While much of the course will be algorithmic in nature, you will still need to be able to prove theorems.

## Keywords

Linear Programming, Algorithms, Complexity, Graphs, Optimization

Linear Algebra

## Recommended courses

Discrete Mathematics or Discrete Structures

## Important concepts to start the course

The student needs to be comfortable reading and writing formal mathematical proofs.

## Learning Outcomes

By the end of the course, the student must be able to:

• Choose appropriate method for solving basic discrete optimization problem
• Prove basic theorems in linear optimization
• Interpret computational results and relate to theory
• Implement basic algorithms in linear optmization
• Describe methods for solving linear optimization problems
• Create correctness and running time proofs of basic algorithms
• Solve basic linear and discrete optimization problems

## Transversal skills

• Continue to work through difficulties or initial failure to find optimal solutions.
• Use both general and domain specific IT resources and tools

## Teaching methods

Ex cathedra lecture, exercises in the classroom and with a computer

## Expected student activities

• Attendance of lectures and exercises
• Completion of exercises
• Solving supplementary programs with the help of a computer

## Assessment methods

Written exam during the exam session

## Bibliography

Dimitris Bertsimas and John N. Tsitsiklis: Introduction to Linear Optimization, Athena Scientific

Lecture notes

## Dans les plans d'études

• Semestre: Printemps
• Forme de l'examen: Ecrit (session d'été)
• Matière examinée: Discrete optimization
• Cours: 2 Heure(s) hebdo x 14 semaines
• Exercices: 2 Heure(s) hebdo x 14 semaines
• Semestre: Printemps
• Forme de l'examen: Ecrit (session d'été)
• Matière examinée: Discrete optimization
• Cours: 2 Heure(s) hebdo x 14 semaines
• Exercices: 2 Heure(s) hebdo x 14 semaines
• Semestre: Printemps
• Forme de l'examen: Ecrit (session d'été)
• Matière examinée: Discrete optimization
• Cours: 2 Heure(s) hebdo x 14 semaines
• Exercices: 2 Heure(s) hebdo x 14 semaines
• Semestre: Printemps
• Forme de l'examen: Ecrit (session d'été)
• Matière examinée: Discrete optimization
• Cours: 2 Heure(s) hebdo x 14 semaines
• Exercices: 2 Heure(s) hebdo x 14 semaines
• Semestre: Printemps
• Forme de l'examen: Ecrit (session d'été)
• Matière examinée: Discrete optimization
• Cours: 2 Heure(s) hebdo x 14 semaines
• Exercices: 2 Heure(s) hebdo x 14 semaines
• Semestre: Printemps
• Forme de l'examen: Ecrit (session d'été)
• Matière examinée: Discrete optimization
• Cours: 2 Heure(s) hebdo x 14 semaines
• Exercices: 2 Heure(s) hebdo x 14 semaines

## Semaine de référence

 Lu Ma Me Je Ve 8-9 9-10 10-11 11-12 12-13 13-14 14-15 15-16 16-17 17-18 18-19 19-20 20-21 21-22