MATH-261 / 5 credits

Teacher: Pinchasi Rom

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.

## 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

Dans le cas de l'art. 3 al. 5 du Règlement de section, l'enseignant décide de la forme de l'examen qu'il communique aux étudiants concernés.

## Bibliography

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

Lecture notes

## In the programs

• Semester: Spring
• Exam form: Written (summer session)
• Subject examined: Discrete optimization
• Lecture: 2 Hour(s) per week x 14 weeks
• Exercises: 2 Hour(s) per week x 14 weeks
• Semester: Spring
• Exam form: Written (summer session)
• Subject examined: Discrete optimization
• Lecture: 2 Hour(s) per week x 14 weeks
• Exercises: 2 Hour(s) per week x 14 weeks
• Semester: Spring
• Exam form: Written (summer session)
• Subject examined: Discrete optimization
• Lecture: 2 Hour(s) per week x 14 weeks
• Exercises: 2 Hour(s) per week x 14 weeks
• Semester: Spring
• Exam form: Written (summer session)
• Subject examined: Discrete optimization
• Lecture: 2 Hour(s) per week x 14 weeks
• Exercises: 2 Hour(s) per week x 14 weeks
• Semester: Spring
• Exam form: Written (summer session)
• Subject examined: Discrete optimization
• Lecture: 2 Hour(s) per week x 14 weeks
• Exercises: 2 Hour(s) per week x 14 weeks
• Semester: Spring
• Exam form: Written (summer session)
• Subject examined: Discrete optimization
• Lecture: 2 Hour(s) per week x 14 weeks
• Exercises: 2 Hour(s) per week x 14 weeks

## Reference week

 Mo Tu We Th Fr 8-9 CM1105 9-10 10-11 CM1105 11-12 12-13 13-14 14-15 15-16 16-17 17-18 18-19 19-20 20-21 21-22

Tuesday, 8h - 10h: Exercise, TP CM1105

Tuesday, 10h - 12h: Lecture CM1105