| Course label : | Operational research |
|---|---|
| Teaching departement : | MIN / Applied Mathematics and General Computing |
| Teaching manager : | Mister DIEGO CATTARUZZA / Mister MAXIME OGIER |
| Education language : | French |
| Potential ects : | 0 |
| Results grid : | |
| Code and label (hp) : | IE4_OFLU_MIN_ROP - Recherche opérationnelle |
Education team
Teachers : Mister DIEGO CATTARUZZA / Mister MAXIME OGIER
External contributors (business, research, secondary education): various temporary teachers
Summary
The objective of the Operational Research course is to be able to model and solve an optimization problem. More precisely, we are interested in minimizing an objective (costs, deadlines,...), taking into account a set of constraints (limitation of available resources, incompatibilities,...). This type of problem is frequently encountered in the fields of transportation (fastest itinerary, vehicle routing), production (planning in a workshop), network design (motorway, train, electricity). The two main tools presented in this course are linear programming and graphs.
Educational goals
At the end of the course, the student will be able to: - Model a problem as a linear program - Graphically solve a linear program with two variables - Perform a sensitivity analysis on a linear program with two variables - Use a commercial solver to solve a linear program - Use the vocabulary of graph theory - Model a problem with a graph - Solve a minimum spanning tree problem - Solve a shortest path problem - Solve a maximum flow problem Contribution of the course to the competency framework (see RNCP sheet); at the end of the course, the student will have progressed in: - Recommend improvements in organization, management, procedures o Ability to analyze a problem o Ability to model an optimization problem o Ability to solve an optimization problem
Sustainable development goals
Knowledge control procedures
Continuous Assessment
Comments: The evaluation consists in 1 final exam during 2 hours at the end of the course. This evaluation represents 100% of the final grade.
Online resources
Resources are the subjects provided to students at the beginning of each class.
Pedagogy
1) 2h lecture: Amphi Presentation of Operational Research + Linear Programming 2) 2h tutorial: TD Room Linear Program Modeling 3) 2h tutorial: TD Room Sensitivity analysis 4) 2h lecture: Amphi Graphs and applications 5) 2h tutorial: TD Room Graphs vocabulary 6) 2h tutorial: TD Room Shortest path problem and maximum flow problem 7) 2h TD: DP, TD Room Solving problems with graphs 8) 4h labs: machine room Use of a commercial LP solver 9) 2h exam Final evaluation
Sequencing / learning methods
| Number of hours - Lectures : | 4 |
|---|---|
| Number of hours - Tutorial : | 6 |
| Number of hours - Practical work : | 4 |
| Number of hours - Seminar : | 0 |
| Number of hours - Half-group seminar : | 4 |
| Number of student hours in TEA (Autonomous learning) : | 0 |
| Number of student hours in TNE (Non-supervised activities) : | 4 |
| Number of hours in CB (Fixed exams) : | 0 |
| Number of student hours in PER (Personal work) : | 0 |
| Number of hours - Projects : | 0 |
Prerequisites
To follow this course, it is necessary to have a basic knowledge of mathematics: linear functions (definition, representation in dimension 2), and the resolution of systems of equations. Knowledge of algorithms is also required.
Maximum number of registrants
Remarks
The lab (class 8) must be placed after class 3 and before class 9. It is possible to have the tutorial classes in parallel for the two groups.