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| MQGE0002-3 | Advanced Operations Research
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| Duration : | 30h Th |
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| Number of credits : |
| Master in Business Engineering, didactic approach, 1st year | | First semester | | 5 |
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| Master degree in Business Engineering, professional Focus in Financial Engineering, 1st year | | First semester | | 5 |
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| Master in Management Engineering, professional Focus, 1st year | | First semester | | 5 |
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| Master en ingénieur de gestion, à finalité spécialisée en intrapreneuriat, 1st year | | First semester | | 5 |
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| Master en ingénieur de gestion, à finalité spécialisée en Modélisation et technologie, 1st year | | First semester | | 5 |
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| Master in Business Engineering, professional Focus in Supply Chain Management, 1st year | | First semester | | 5 |
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| Master en ingénieur de gestion, à finalité spécialisée en performance management systems, 1st year | | First semester | | 5 |
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| Lecturer : | Yves Crama |
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Language(s) of instruction :
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| English language |
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Course contents :
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| The aim of this course is to present various aspects of mathematical modeling and of problem-solving strategies as they are used in operations research for the solution of realistic, large-scale, complex problems.
The course contains several independent parts:
- General-purpose heuristic strategies for the solution of combinatorial optimization problems, such as simulated annealing, tabu search or genetic algorithms; the practical implementation of such methods is illustrated on a variety of optimization problems.
- Integer programming problems. Branch-and-bound method. Modeling and solution of large-scale models by means of a special-purpose modeling language (that is, a computer language specially devoted to the formulation, the solution and the analysis of large-scale optimization models).
- As time allows: other numerical methods, such as simulation, neural networks, constraint programming, etc. |
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Learning outcomes of the course :
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| By the end of this course, the students will be able to model complex decision-making problems and to implement appropriate methods for their solution. They will better understand the opportunities offered by optimization methods, as well as their intrinsic limitations.
As a side-benefit, they will also develop advanced computer programming skills that are transferable to different business contexts. |
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Prerequisites and co-requisites/ Recommended optional programme components :
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| Prerequisites:
- Mathematics: calculus and matrix algebra.
- Operations research: an introductory course covering linear programming models and methods.
- General proficiency with personal computers.
- Command of a computer programming language (MathLab, SciLab, Pascal, C, Visual Basic,...) is an asset. An introduction to SciLab will be provided for those students who choose to use this language for the development of their projects. |
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Planned learning activities and teaching methods :
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| Group and individual projects: computer implementations, written reports and oral presentations. |
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Mode of delivery (face-to-face ; distance-learning) :
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| Lectures and computer labs. Group and individual projects: computer implementations, reports and presentations. Attendance is mandatory. |
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Recommended or required readings :
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| Lecture notes:
Y. Crama, Advanced Operations Research, ULg. |
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Assessment methods and criteria :
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| The final note will be based on the evaluation of the projects (written reports and oral presentations).The oral presentations will take place during the examination session of January 2012. |
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Organizational remarks :
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| This course is taught in English.
See the Lola Web site
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)
Phone. : 04 366 30 77
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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