Study programme 2019-2020Français
Optimisation Methods
Programme component of Master's in Computer Engineering and Management (Charleroi (Hor. décalé)) à la Faculty of Engineering

Students are asked to consult the ECTS course descriptions for each learning activity (AA) to know what assessment methods are planned for the end of Q3

CodeTypeHead of UE Department’s
contact details
UI-M1-IRIGIG-891-COptional UETUYTTENS DanielF151 - Mathématique et Recherche opérationnelle
  • TUYTTENS Daniel

of instruction
of assessment
HT(*) HTPE(*) HTPS(*) HR(*) HD(*) CreditsWeighting Term
  • Français
Français241600044.001st term

AA CodeTeaching Activity (AA) HT(*) HTPE(*) HTPS(*) HR(*) HD(*) Term Weighting
I-MARO-152Optimisation Methods2416000Q1100.00%
Programme component

Objectives of Programme's Learning Outcomes

  • Imagine, design, develop, and implement conceptual models and computer solutions to address complex problems including decision-making, optimisation, management and production as part of a business innovation approach by integrating changing needs, contexts and issues (technical, economic, societal, ethical and environmental).
    • Deliver a solution selected in the form of diagrams, graphs, prototypes, software and/or digital models.
    • Evaluate the approach and results for their adaptation (modularity, optimisation, quality, robustness, reliability, upgradeability, etc.).
  • Mobilise a structured set of scientific knowledge and skills and specialised techniques in order to carry out computer and management engineering missions, using their expertise and adaptability.
    • Master and appropriately mobilise knowledge, models, methods and techniques specific to computer management engineering.
    • Identify and discuss possible applications of new and emerging technologies in the field of information technology and sciences and quantifying and qualifying business management.
    • Assess the validity of models and results in view of the state of science and characteristics of the problem.
  • Communicate and exchange information in a structured way - orally, graphically and in writing, in French and in one or more other languages - scientifically, culturally, technically and interpersonally, by adapting to the intended purpose and the relevant public.
    • Argue to and persuade customers, teachers and boards, both orally and in writing.
    • Use and produce scientific and technical documents (reports, plans, specifications) adapted to the intended purpose and the relevant public.
  • Adopt a professional and responsible approach, showing an open and critical mind in an independent professional development process.
    • Exploit the different means available in order to inform and train independently.

Learning Outcomes of UE

study the numerical methods for solving the problem in which one seeks to minimize or maximize a linear real objective function submitted  to linear equality or inequality constraints (both continuous and discrete cases are considered);understand the working of the optimization methods; choose the adequate method for solving a given optimization problem;be sensitive to the optimization problems existing in the industrial world;be aware of the growing complexity of the problems and the evolution of the optimization techniques.

Content of UE

Continuous linear programming (real variables) : Simplex algorithm; duality; dual algorithm;Integer linear programming (discrete variables) : Branch and Bound algorithm; Combinatorial optimization; extensions and problem modelling.Revised Simplex algorithm; treatment of bounded variables ; sensitivity analysis; modelling of linear problems; use of an optimization tool (Excel solver).

Prior Experience

properties of vector spaces; solving systems of linear equations

Type of Assessment for UE in Q1

  • Written examination

Q1 UE Assessment Comments

Written examination covering all parts of the course, including short questions on theory and some exercises. Part   1 : Theory 45% Part   2 : Exercises 45% Part 3 : Modelling 10%

Type of Assessment for UE in Q3

  • Written examination

Q3 UE Assessment Comments

Written examination covering all parts of the course, including short questions on theory and some exercises. Part   1 : Theory 45% Part   2 : Exercises 45% Part 3 : Modelling 10%

Type of Resit Assessment for UE in Q1 (BAB1)

  • N/A

Q1 UE Resit Assessment Comments (BAB1)

Not applicable

Type of Teaching Activity/Activities

AAType of Teaching Activity/Activities
  • Cours magistraux
  • Ateliers et projets encadrés au sein de l'établissement

Mode of delivery

AAMode of delivery
  • Face to face

Required Reading


Required Learning Resources/Tools

AARequired Learning Resources/Tools
I-MARO-152Not applicable

Recommended Reading

AARecommended Reading
I-MARO-152Copie de présentation - Méthodes d'optimisation - D. Tuyttens

Recommended Learning Resources/Tools

AARecommended Learning Resources/Tools
I-MARO-152Not applicable

Other Recommended Reading

AAOther Recommended Reading
I-MARO-152Teghem, J., Programmation linéaire, Editions de l'ULB, Editions Ellipses, Bruxelles, 2003 Guéret C., Prins C. et Sevaux M. 2000, Programmation linéaire, Editions Eyrolles,.

Grade Deferrals of AAs from one year to the next

AAGrade Deferrals of AAs from one year to the next
(*) HT : Hours of theory - HTPE : Hours of in-class exercices - HTPS : hours of practical work - HD : HMiscellaneous time - HR : Hours of remedial classes. - Per. (Period), Y=Year, Q1=1st term et Q2=2nd term
Date de génération : 13/07/2020
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