Premier quadrimestre, 26 heures de théorie.

Anglais

Learning outcomes to be attained
1 Is able to relate theory to practice
2 Can develop a reasoning that corresponds to the (domain-specific) scientific requirements
3 Reflects critically on the achievements and the limitations of the own discipline
4 Can identify, model and analyse the results of a discipline-related problem
5 Can gain insight in a complex situation and link the parts of a problem to each other
6 Knows the techniques and methods of research and knows how to implement them adequately
7 Is able to interpret a problem in its context
8 Integrates nformation technology to come to solutions
9 Has insight in a basic set of concepts and methods within the domain of operations research, econometrics and multivariate data-analysis and their application
10 Is able to use mathematical, statistical and research methods in order to set up models for analysing business problems in different domains (natural sciences, technology, economics, business economics,...)
11 Is able to use his knowledge of mathematics, statistics and research methods to judge information and results ofbusiness problems in a critical way in different domains (natural sciences, technology, economics, business economics,...)
12 Is able to use ICT-tools as an aid in modelling research problems and in analysing and presenting their results

Key objectives of the course
1. The student is able to recognize and formulate (mathematically and/or in optimization software) linear programming problems.
2. The student is able to solve linear programming problems. The student understands how and why the solution methodologies work.
3. The student is able to interpret the optimal solution (and corresponding output of optimization software) and understands how changes in inputdata and assumptions affect the optimal solution.

Pour le programme de Bachelor of Science in Business Engineering :

Aucun

1. Introduction to management science
2. Introduction to linear programming (graphical solution, workforce scheduling, capital budgeting, short term financial planning, blending problems, production process models, multiperiod models)
3. The simplex algorithm
4. Duality
5. Sensitivity analysis
6. LINDO, CPLEX and MS Excel Solver

Interactive formal lectures:
During formal lectures the theoretical knowledge will be dealt with in detail. The students are expected to interact (lively).

Self-study:
The compulsory course material offers the students the possibility to accumulate their knowledge independently. The students are expected to make some homeworks.

Exercises:
Students will complete exercises, as an extension of the formal lectures.
Software:
The students get familiar with the software tools LINDO, CPLEX and MS Excel Solver.

Type : Partial or continuous assessment with (final) exam during the examination period
Description of evaluation : Written, Skills test
Type of questions : Open questions
Learning material : Calculator

Exam period Jan/Feb or May/Jun
Organization : written
Use learning materials : closed book
Evaluation method : theory test
Question Type : application requests

Explanation :
Students will be evaluated by the professor on the basis of a modelling exercise and a written, closed-book exam. The modelling exercise counts for 20% of the final score, the exam counts for 80% of the final score. The students will have to make some homeworks. These homeworks are not explicitly graded. However, in case of "good" homeworks, the final score is rounded up, otherwise it is rounded down.

Exam period Aug/Sep
Organization : written
Use learning materials : closed book
Evaluation method : theory test
Question Type : application requests

Explanation :
Students will be evaluated by the professor solely on the basis of a written exam. There is no modelling exercise for the second exam period. Homeworks are not taken into account for the Aug/Sep exam.

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