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| MQGE0001-1 | Operations Research
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| Duration : | 24h Th |
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| Credits/ECTS : |
| Master in Economical Sciences, in-depth approach, 1st year | | Premier quadrimestre | | 5 |
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| Master in Economical Sciences, didactic approach, 1st year | | Premier quadrimestre | | 5 |
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| Master in Business Engineering, didactic approach, 1st year | | Premier quadrimestre | | 4 |
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| Master in Economical Sciences, Professional Focus in Economic Policies and Analysis, 1st year | | Premier quadrimestre | | 5 |
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| Master in Management Engineering, professional Focus, 1st year | | Premier quadrimestre | | 4 |
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| Holder(s) : | Yves Crama |
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| Language : | Langue anglaise |
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| Course contents : | 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;
* simulation : basic principles, random generators, analysis of results.
The course is illustrated by numerous examples and applications. |
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| Course objective : | 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 modelling approach. |
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| Prerequisites : | Mathematics (linear algebra, matrix algebra), probability theory and statistics (concept of random variable, classical distributions, expectation, variance, etc.). |
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| Organization : | (Tentative plan)
A1. Lectures.
A1. Readings (lecture notes and case studies).
A2. Numerical exercises and computer labs.
A3. Mini-project (formulation and resolution of a small case; to be confirmed). |
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| Written notes : | 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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| Assessment : | Written examination during the period immediately following the end of the course.
The evaluation of the mini-project contributes -1, 0, or +1 point to the final grade. |
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| Contacts : | Instructor: Y. CRAMA
HEC-Management School (Bât. B31)
Phone. : 04 366 30 77
Email : Y.Crama@ulg.ac.be
Teaching assistant: M. BAY
HEC-Management School (Bât. B31)
Phone : 04 366 31 05
Email : Maud.Bay@ulg.ac.be |
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| Remarks : | The course is taught in English. |
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| Items online : |
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| Course material |
| All relevant course material can be found on the e-learning campus "Lola" of HEC-ULg. |
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