Fiches de cours 2017-2018

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Optimal decision making

MGT-483

Enseignant(s) :

Kuhn Daniel

Langue:

English

Summary

This course introduces the theory and applications of optimization. We develop tools and concepts of optimization and decision analysis that enable managers in manufacturing, service operations, marketing, transportation and finance to transform data into insights for making better decisions.

Content

Fundamental techniques covered in this course include linear, discrete and nonlinear optimization. The underlying theory is motivated through concrete examples across several application areas such as project management, portfolio selection, production planning, revenue management, transportation, etc. We will use MATLAB to model and solve practical decision problems.

The following topics will tentatively be covered in the course:

Part I: Linear Optimization

Part II: Discrete Optimization

Part III: Nonlinear Optimization

Keywords

Linear optimization, discrete optimization, nonlinear optimization

Learning Prerequisites

Important concepts to start the course

A good background in linear algebra and calculus is required. Basic knowledge of probability theory is useful but not necessary.

Learning Outcomes

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

Transversal skills

Teaching methods

Classical formal teaching interlaced with practical exercices

Assessment methods

Exams are closed book and on paper (no use of computer)

Supervision

Office hours Yes
Assistants Yes

Resources

Bibliography

  1. Dimitris Bertsimas and John Tsitsiklis, Introduction to Linear Optimization, Dynamic Ideas & Athena Scientific, 2008.
  2. Dimitri P. Bertsekas, Nonlinear Programming, Athena Scientific, 2004.

Ressources en bibliothèque

Dans les plans d'études

  • Génie électrique et électronique , 2017-2018, Master semestre 1
    • Semestre
      Automne
    • Forme de l'examen
      Ecrit
    • Crédits
      4
    • Matière examinée
      Optimal decision making
    • Cours
      2 Heure(s) hebdo x 14 semaines
    • Exercices
      2 Heure(s) hebdo x 14 semaines
  • Génie électrique et électronique , 2017-2018, Master semestre 3
    • Semestre
      Automne
    • Forme de l'examen
      Ecrit
    • Crédits
      4
    • Matière examinée
      Optimal decision making
    • Cours
      2 Heure(s) hebdo x 14 semaines
    • Exercices
      2 Heure(s) hebdo x 14 semaines
  • Management, technologie et entrepreneuriat, 2017-2018, Master semestre 1
    • Semestre
      Automne
    • Forme de l'examen
      Ecrit
    • Crédits
      4
    • Matière examinée
      Optimal decision making
    • Cours
      2 Heure(s) hebdo x 14 semaines
    • Exercices
      2 Heure(s) hebdo x 14 semaines
  • Management, technologie et entrepreneuriat, 2017-2018, Master semestre 3
    • Semestre
      Automne
    • Forme de l'examen
      Ecrit
    • Crédits
      4
    • Matière examinée
      Optimal decision making
    • Cours
      2 Heure(s) hebdo x 14 semaines
    • Exercices
      2 Heure(s) hebdo x 14 semaines
  • Mineur en Management, technologie et entrepreneuriat, 2017-2018, Semestre automne
    • Semestre
      Automne
    • Forme de l'examen
      Ecrit
    • Crédits
      4
    • Matière examinée
      Optimal decision making
    • Cours
      2 Heure(s) hebdo x 14 semaines
    • Exercices
      2 Heure(s) hebdo x 14 semaines
  • Mineur en Systems Engineering, 2017-2018, Semestre automne
    • Semestre
      Automne
    • Forme de l'examen
      Ecrit
    • Crédits
      4
    • Matière examinée
      Optimal decision making
    • Cours
      2 Heure(s) hebdo x 14 semaines
    • Exercices
      2 Heure(s) hebdo x 14 semaines

Semaine de référence

LuMaMeJeVe
8-9
9-10
10-11
11-12
12-13
13-14MA B1 11
14-15
15-16MA B1 11
16-17
17-18
18-19
19-20
20-21
21-22
Cours
Exercice, TP
Projet, autre

légende

  • Semestre d'automne
  • Session d'hiver
  • Semestre de printemps
  • Session d'été
  • Cours en français
  • Cours en anglais
  • Cours en allemand