Objectives of Programme's Learning Outcomes

• Implement an engineering approach dealing with a set problem taking into account technical, economic and environmental constraints
• Identify and acquire the information and skills needed to solve the problem
• Understand the theoretical and methodological fundamentals in science and engineering to solve problems involving these disciplines
• Identify, describe and explain basic scientific and mathematical principles
• Identify, describe and explain the basic principles of engineering particularly in their specialising field
• Understand laboratory techniques: testing, measuring, monitoring protocol, and security
• Select and rigorously apply knowledge, tools and methods in sciences and engineering to solve problems involving these disciplines
• Communicate in a structured way - both orally and in writing, in French and English - giving clear, accurate, reasoned information
• Argue to and persuade customers, teachers and a board both orally and in writing
• Demonstrate thoroughness and independence throughout their studies
• Identify the different fields and participants in engineering
• Develop their scientific curiosity and open-mindedness
• Learn to use various resources made available 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).

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

Type of Assessment for UE in Q1

• Written examination

Q1 UE Assessment Comments

Written examination in person covering all parts of the course, including short questions on theory and some exercises. Part   1 : Theory and  Part  2 : Exercises  [=90% of the evaluation] and Part 3 : Modelling  [=10% of the evaluation]

The evaluation procedures are likely to be adjusted according to
the educational/assessment context imposed by health measures.

Type of Assessment for UE in Q3

• Written examination

Q3 UE Assessment Comments

Written examination in person covering all parts of the course, including short questions on theory and some exercises. Part   1 : Theory and  Part  2 : Exercises  [=90% of the evaluation] and Part 3 : Modelling  [=10% of the evaluation]

The evaluation procedures are likely to be adjusted according to
the educational/assessment context imposed by health measures.

Type of Resit Assessment for UE in Q1 (BAB1)

• N/A

Q1 UE Resit Assessment Comments (BAB1)

Not applicable