Ce cours apparaît dans les formations suivantes :
• IÉSEG > MSc in Big Data Analytics for Business > Semester 2 > 2,00 ECTS

Pré requis

This is a mathematically and computationally oriented course, where students are expected to have previously completed basic courses in Differential and Integral Calculus, Linear Algebra, and Computer Programming.

Objectifs du cours

At the end of the course, the student should be able to:
- understand the different mathematical programming modeling strategies (linear, nonlinear, integer)
- design mathematical programming models for supply chain management, logistic, transportation, portfolio selection and pricing
- understand the different algorithmic methods for linear, nonlinear and integer optimization
- solve optimization problems using specialized softwares

These competencies and/or skills contribute to the following learning objectives
- 3.A Breakdown complex organizational problems using the appropriate methodology
- 5.B Construct expert knowledge from cutting-edge information
- 5.D. Make effectual organizational decisions
- 7.B Formulate strategically-appropriate solutions to complex and unfamiliar challenges in their professional field

Contenu du cours

This is a graduate course in Optimization, which is designed to enable students to correctly model and solve linear, nonlinear and integer optimization problems. The first part of the course is oriented to the analysis of the different mathematical programming modeling strategies. The second part of the course focuses on algorithms and provides students with a collection of computational tools to correctly solve the designed models. The course is based on the use of several computational methods. Optimization software, such as AMPL, R and MINOS are presented.

Modalités d'enseignement

Organisation du cours

Méthodes pédagogiques

• Interactive class
• Presentation
• Project work
• Research

Évaluation

The students evaluation is based on an individual assignment, a group project and the participation.