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.

UE Content: description and pedagogical relevance

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).

The teaching methods are likely to be adjusted according to the educational context
imposed by the health measures.


 

Prior Experience

properties of vector spaces; solving systems of linear equations