Learning outcomes

This course is an introduction to Operational Research and aims at teaching students how to model typical business optimization problems. At the end of the course, students should be able to (i) identify typical problems in operational research, (ii) solve the problems using methods developed during the class, (iii) display critical thinking to interpret the obtained results. The course will have an important theoretical side, thus allowing student to develop the rigor that is needed to solve encountered problems. Lastly, students should be able to solve many problems by hand or using Excel, and proceed with a clear analysis.

Goals

The course objectives are

1) Write problems as linear pograms or combinatorial problems on graphs. 

2) Use the appropriate algorithms to solve these problems. 

3) Study the theoretical properties (consistency, etc.) of the algorithms used. 

4) If necessary, develop heuristics to find approximate solutions.

Content

Content of the course is the following:
  1. Introduction to operations research.
  2. Linear programming : definitions, geometrical properties, simplex algorithm, sensisitivity analysis, dual theory and economic interpretation.
  3. Integer linear programming: definitions, properties, Branch-and-Bound, cuts. Introduction to metaheuristics.
  4. Combinatorial problems on graphs.

Exercices

Six to seven exercice sessions will be held. Video or paper solutions will be made available after the sessions.

Assessment method

The final grade will solely be based on the results of the exam. The exam is a closed book exam with a 30% theory-70% exercises balance. 

Sources, references and any support material

Notes will be provided on Webcampus. They include the slides and associated recordings, as well as a syllabus (made available during the semester).

Language of instruction

Français
Training Study programme Block Credits Mandatory
Standard 0 4
Standard 0 5
Standard 3 4