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Analytics in Operations Management

  • Teacher(s):   V.Lurkin  
  • Course given in: English
  • ECTS Credits: 3 credits
  • Schedule: Spring Semester 2021-2022, 2.0h. course (weekly average)
  •  sessions
  • site web du cours course website
  • Related programmes:
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    Master of Science (MSc) in Management, Orientation Business Analytics

    Master of Science (MSc) in Management, Orientation Strategy, Organization and Leadership

    Master of Science (MSc) in Management, Orientation Marketing
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Objectives

This master course focuses on the application of scientific and mathematical methods to study and analzye operations management problems.

In this course, we will cover problems that arise because of a mismatch between demand and supply, with respect to their timing and/or their quantities.

At the end of the course, students are expected to:

  • Understand how and when the tools of operations management can be applied to solve inventory and scheduling problems.
  • Understand the mathematical modeling behind these problems.
  • Solve these models using various operations management tools.
  • Analyze the results and draw lessons for the operational management perspective.

The course is given in Anthropole 3128 on Wednesday morning from 8:30 to 12:00 until April 6th (first 7 weeks of the semester).

Each session starts with a lecture of around 1:30/2h and is followed by a lab session of 1:30/2h.

Students need to bring their computer to class.

Contents

The course is organized around the following sessions:

- General introduction on operations management problems

- Deterministic inventory problems

- Stochastic inventory problems

- Scheduling on a single machine

- Scheduling on a parallel machine

- Job shop scheduling

- Batch scheduling

References

The 4th Edition of Matching Supply with Demand: An Introduction to Operations Management by Gerard Cachon and Christian Terwiesch.

Pre-requisites

The optimization and operations management courses from the bachelor program.

Some experience with Google OR-tools is welcome.

https://developers.google.com/optimization

Evaluation

First attempt

Exam:
Without exam (cf. terms)  
Evaluation:

The students will work in groups on two projects. Final grade will be the weighted average of these projects.

Retake

Exam:
Oral 20 minutes
Documentation:
Not allowed
Calculator:
Not allowed
Evaluation:

An individual oral evaluation will take place for students who did not obtain a 4.0 for their projects.



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