Code
MGFE OPM 5155
Niveau
M2
Discipline
Logistique, supply chain, etc.
Langue
Anglais/English
Crédits ECTS
1
Heures programmées
12
Charge totale étudiant
20
Equipe pédagogique
Introduction au module
Supply chains are an important part of businesses. As described by the Council of Supply Chain Management Professionals, “Supply chain management is an integrating function with primary responsibility for linking major business functions and business processes within and across companies into a cohesive and high-performing business model”. With the advancement of digitalisation, decision-making in supply chains has not only become more powerful, but also more complex due to the large scale of problems. This course introduces three main methodologies in resolving business challenges that leverage digitalization of the supply chain: Network Science, Optimization, and Game Theory.
Bloc de compétences
- 1. S’approprier les usages avancés et spécialisés des outils de l’intelligence digitale en s’assurant de leur impact durable et responsable
Compétences du bloc
- 1 - Connaissances disciplinaires et raisonnement
- 1.1 - Connaissance des sciences de base, y compris mathématiques et autres
- 1.2 - Connaissance des principes fondamentaux d'ingénierie
Objectifs d'apprentissage du cours
By the end of this course, the students will acquire the key concepts of network science, optimisation methods, and game theory. They will be able to identify how problems in supply chain management can be solved using these methodologies. They will be able to deduce the main problems in case studies and illustrative examples, analyse data to solve the problem, and justify how their results translate to managerial decisions in businesses.
Contenu : structure du module et agenda
The 18 hours of the course are roughly scheduled in the following order:
Networks – 5 hours
First Written Exam – 1 hour
Optimisation – 5 hours
Second Written Exam – 1 hour
Game Theory – 4 hours
Case Presentations – 2 hours
Contribution à l'atteinte des ODD (Objets du Développement Durable)
This course addresses Goal 9 (Industry, Innovation, and Infrastructure) of the UN Sustainable Development Goals. Specifically focusing on the developments in technical capabilities of the industrial sector, in this case supply chain enterprises.
Nombre d'ODD abordés parmi les 17
1
Apprentissage
synchrone
Méthode pédagogique
This course is delivered through synchronous lectures combining case studies and numerical exercises. Students are assessed individually through written exams as well as collaboratively through a group case report and presentation. Active participation is encouraged, with students posing questions to the instructor and responding to questions posed in class.
Système de notation et modalités de rattrapage
The students are evaluated with the following rubrics:
Class Participation – 10%
2 In-Class Written Exams – 30%
1 Group Case Study – 30%
1 Final Written Exam – 30%
For class participation, students are expected to actively ask questions to the teachers and answer questions in class. They are encouraged to discuss ideas with each other. The first and second written exam will consist of questions related to materials taught in class. It will include questions where students may have to analyse data, explain concepts, and argue how they would use the results to make management decisions. A case study will be assigned to be solved in groups. Students will have to submit a written report for the case study as well as present their findings and insights in front of the teacher and other students. The teacher will ask the students follow-up oral questions based on their report and presentation. The final exam will be a written exam as well. If a student does not achieve a score of at least 10 out of 20 on this evaluation, a remedial exam will be administered. This exam will be a written exam and will count for 100% of the final grade.
Règlement du module
Professor-Student Communication:
The professor will contact students only through their school email address and the Moodle portal; no communication will take place via personal email addresses. Students are responsible for checking their IMT-BS/TSP mailbox regularly. To reach the professor, students should email their institutional address. Meetings can also be arranged by appointment.
Accommodating Student Needs:
Students with a disability that may prevent them from completing coursework, or who require any accommodation, should inform the program director as soon as possible (with supporting documentation). Students are also encouraged to discuss their situation directly with the professor as well.
Class Behaviour:
Out of respect for the professor and fellow students, all phones, electronic games, and other sound-generating devices must be switched off during class. Students should avoid disruptive or disrespectful behaviour, including but not limited to arriving late, leaving early, sleeping, reading non-course material, using inappropriate language, talking over others, or eating and drinking in class. A warning will be issued for a first offence; repeated violations may result in penalties, expulsion from class, and/or further disciplinary action. A grace period of 5 minutes is allowed for tardiness. Attendance is recorded on Edusign during this window via a QR code provided at the start of class. Students must arrive on time for exams and other assessments. Once the first student has finished and left the exam room, no one else may enter; there is no exception to this rule. No student may continue working once time is up, and no student may leave the room during an examination unless they have finished and submitted all materials.
Honor Code:
IMT-BS upholds a strict policy of academic honesty. Any conduct that compromises this policy may result in academic and/or disciplinary sanctions. Students must not cheat, lie, plagiarise, or misrepresent others' work as their own. This means submitting original work and properly crediting any ideas or material that are not one's own, including materials paraphrased, quoted, or taken from the internet. This also means disclosing any use of AI in an assignment, including details on how it was used. Any student who violates, or assists another student in violating, these academic standards will be penalised according to IMT-BS policy.
Références obligatoires et lectures suggérées
Barabási, A. L. “Network Science”, Cambridge University Press.
Bertsimas, D., Tsitsiklis, J. “Introduction to Linear Optimization”, Athena Scientific.
Osborne, M. "Introduction to Game Theory", Oxford University Press.
Mots-clés
Supply Chain Management, Networks, Optimisation, Game Theory
Prérequis
basics of probability and statistics, linear algebra