CIVIL-557 / 4 crédits

Enseignant(s): Paschalidis Evangelos, Torres Duran Fabian Alejandro

Langue: Anglais

Remark: The course is given by various lecturers


Summary

The course proposes an introduction to operations research, and mathematical modelling for decision support in transportation systems.

Content

Keywords

Operations research, behavioural modelling, trasnportation.

Learning Prerequisites

Required courses

Indtoduction to optimization and operations research( CIVIL-265 ),  Recherche opérationnelle,

Recommended courses

Introduction to python.

Important concepts to start the course

The Simplex Algorithm, Integer programming. Knowledge of python. Statistics and regression modelling.   Some knowledge of commercial solvers like CPLEX and Gurobi.

Learning Outcomes

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

  • Model decision processes in transportation systems as optimization problems.
  • Implement and solve optimization problems using state-of-the-art solvers.
  • Know and understand various optimization approaches.
  • Model decision processes in transportation systems as optimization problems
  • and solve optimization problems using state-of-the-art solvers, i.e., CPLEX.
  • Choose an appropriate optimization approach.
  • Analyze data using state-of-the-art mathematical methods.
  • Choose an appropriate data analysis and modelling approach.

Teaching methods

The optimization, data analysis and modelling approaches will be presented and applied to real world case studies during lectures. The students will apply the methods learnt in class during the laboratory sessions and work in groups on a project with real data.

Assessment methods

  • At the end of each module, each group will submit a project report.
  • At the end of the course, each group will present the project during an oral exam. The assessment will be based on the quality of the report, the quality of the presentation and the answers to the questions. The oral exam will account for 80% of the final grade.
  • At the end of the course, each student will complete a written exam. The written exam will include multiple choice and short answer questions, and it will account for 20% of the final grade.

Resources

Ressources en bibliothèque

    Moodle Link

    Dans les plans d'études

    • Semestre: Printemps
    • Forme de l'examen: Pendant le semestre (session d'été)
    • Matière examinée: Decision-aid methodologies in transportation
    • Cours: 2 Heure(s) hebdo x 14 semaines
    • Exercices: 2 Heure(s) hebdo x 14 semaines
    • Semestre: Printemps
    • Forme de l'examen: Pendant le semestre (session d'été)
    • Matière examinée: Decision-aid methodologies in transportation
    • Cours: 2 Heure(s) hebdo x 14 semaines
    • Exercices: 2 Heure(s) hebdo x 14 semaines
    • Semestre: Printemps
    • Forme de l'examen: Pendant le semestre (session d'été)
    • Matière examinée: Decision-aid methodologies in transportation
    • Cours: 2 Heure(s) hebdo x 14 semaines
    • Exercices: 2 Heure(s) hebdo x 14 semaines
    • Semestre: Printemps
    • Forme de l'examen: Pendant le semestre (session d'été)
    • Matière examinée: Decision-aid methodologies in transportation
    • Cours: 2 Heure(s) hebdo x 14 semaines
    • Exercices: 2 Heure(s) hebdo x 14 semaines

    Semaine de référence

     LuMaMeJeVe
    8-9 GCB330
    CM1112
       
    9-10    
    10-11 GCB330
    CM1112
       
    11-12    
    12-13     
    13-14     
    14-15     
    15-16     
    16-17     
    17-18     
    18-19     
    19-20     
    20-21     
    21-22     

    Mardi, 8h - 10h: Cours GCB330
    CM1112

    Mardi, 10h - 12h: Exercice, TP GCB330
    CM1112

    Cours connexes

    Résultats de graphsearch.epfl.ch.