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| MQGE0001-4 | Operations Research
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| Durée : | 30h Th |
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| Nombre de crédits : |
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| Nom du professeur : | Yves Crama |
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Langue(s) du cours :
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| Langue anglaise |
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Contenus du cours :
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| Operations research relies on mathematical modeling to formulate and to analyze complex decision problems faced by individuals or organizations. OR models and techniques are found at the core of numerous IT tools used in everyday life and in innovative managerial decision support systems, e.g., GPS-based routing systems, airline reservation and pricing software, production planning and scheduling systems, financial investment optimization systems, etc. In order to make a sensible use of OR tools, the manager needs to understand their full potential as well as their limitations. By getting the most out of these tools, companies may be able to develop innovative solutions and to improve their competitive position.
The course offers an introduction to some of the most successful models and techniques used in operations research:
* linear programming: modeling, simplex method, sensitivity analysis, duality;
* queueing theory: basic features, arrival and service processes, M/M/c models;
* if time allows: simulation : basic principles, random generators, analysis of results.
The course is illustrated by numerous examples and applications. |
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Acquis d'apprentissage (objectifs d'apprentissage) du cours :
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| C1. Acquire some familiarity with the mathematical modeling approach to decision-making, and with fundamental models and methods used in operations research: linear programming, queueing models and simulation.
P2. Be able to reconstruct and to interpret the output of simple models.
P3. Be able to recognize situations where OR techniques can be successfully applied and to formulate simple models.
C4. Gain some understanding of the inherent limitations of the mathematical modeling approach. |
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Prérequis et corequis / Modules de cours optionnels recommandés :
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| Mathematics (linear algebra, matrix algebra), probability theory and statistics (concept of random variable, classical distributions, expectation, variance, etc.). |
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Activités d'apprentissage prévues et méthodes d'enseignement :
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| A1. Lectures.
A1. Readings (lecture notes and case studies).
A2. Numerical exercises.
A2. Computer labs.
A3. Computer-based project: formulation and solution of a small case. |
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Mode d'enseignement (présentiel ; enseignement à distance) :
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| Face-to-face lectures and practice sessions. |
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Lectures recommandées ou obligatoires et notes de cours :
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| Lecture notes:
Y. Crama, Operations Research, ULg, 2007.
Additional material to be found on the virtual campus Lol@:
- articles: A Business Executive's Guide to Modern OR, OR The Productivity Engine, Queueing at Vancouver Airport, etc.
- PowerPoint slides
- exercises
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Modalités d'évaluation et critères :
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| Based on:
- written examination in January 2012.
- small modeling project. |
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Remarques organisationnelles :
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| The course is taught in English.
See Lola virtual campus
http://lola.hec.ulg.ac.be/index.php
for additional information. |
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Contacts :
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| Instructor: Y. CRAMA
HEC-Management School (Building N1)
Email : Y.Crama@ulg.ac.be
Teaching assistant: R. SADRABADI
HEC-Management School (Building N1)
Room 328
Email: M.Rezaei@ulg.ac.be (%20m.rezaei@ulg.ac.be) |
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