Descriptif
Learning about advanced decision support techniques such as Operational Research, Discrete Event Simulation and Data Sciences.
Objectifs pédagogiques
Course 7.1 : Quantitative Models (Operational Research)
- Understand the different problem types to Supply Chain optimization, at the different decision levels, in different physical environment and different modelling approach
- Understand the different components of a mathematical model of a real problem in a Supply Chain
- Be able to create new mathematical programming models from real problems in a Supply Chain and know the tools for optimizing it
- Understand the basic operation of a Supply Chain and take decisions in real-time
Course 7.2 : Discrete Event Simulation
- Understand how to model a discrete event simulation problem
- Be able to implement a simple discrete event simulation problem
- Be able to analyze and criticize the results of a discrete event simulation model
Course 7.3 : Data Sciences
- Understand the main techniques of exploiting and analysing datasets
- Know the main Artificial intelligence tools that can be used in Supply Chain context
- Be able to use such a technique through dedicated software
45 heures en présentiel
réparties en:
- Cours Magistraux : 45
- Projet : heures encadrées présentielles : 45
effectifs minimal / maximal:
5/40Diplôme(s) concerné(s)
Pour les élèves du diplômeManagement of International Lean and Supply chain projects
Fundamental of Supply Chain Management Global Supply Chain Management Demand & Flow Management
Format des notes
Numérique sur 20Littérale/grade européenPour les élèves du diplômeManagement of International Lean and Supply chain projects
Vos modalités d'acquisition :
MCQ Test
Group Case studies
individual Exams
Le rattrapage est autorisé- Crédits ECTS acquis : 9 ECTS
La note obtenue rentre dans le calcul de votre GPA.
Programme détaillé
Course 7.1 : Quantitative Models (Operational Research)
Course 7.2 : Discrete Event Simulation
Course 7.3 : Data Sciences
Mots clés
Operational Research, Analytical Models, Discrete Event Simulation, Machine Learning, Data MiningMéthodes pédagogiques
Face-to-Face sessions, Non Face-to-Face sessions, Exercices, Use CasesSupport pédagogique multimédia