Coursebooks

Discrete optimization

MATH-261

Lecturer(s) :

Marcus Adam Wade

Language:

English

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.

Content

Keywords

Linear Programming, Algorithms, Complexity, Graphs, Optimization

Learning Prerequisites

Required courses

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:

Transversal skills

Teaching methods

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

Expected student activities

Assessment methods

Written exam during the exam session

Resources

Bibliography

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

Ressources en bibliothèque
Notes/Handbook

Lecture notes

In the programs

Reference week

 MoTuWeThFr
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     
Under construction
 
      Lecture
      Exercise, TP
      Project, other

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  • Autumn semester
  • Winter sessions
  • Spring semester
  • Summer sessions
  • Lecture in French
  • Lecture in English
  • Lecture in German