Teacher(s)
Language
English
Prerequisites
The prerequisite(s) for this Teaching Unit (Unité d’enseignement – UE) for the programmes/courses that offer this Teaching Unit are specified at the end of this sheet.
Main themes
This course provides an introduction to mathematical modeling of computational problems. It covers the common algorithms, algorithmic paradigms, and data structures used to solve these problems. The course emphasizes the relationship between algorithms and programming. It pays particular attention on the practical importance of specific classes of optimization problems in management science and motivate the students to develop algorithms to solve them.
Learning outcomes
At the end of this learning unit, the student is able to : | |
| 1 | This course contributes to develop the following competencies.
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Content
This course introduces to algorithmic problem solving. Its main goal is to learn how to model practical problems arising from management engineering by using the most appropriate and efficient data structures, as well as how to implement the most efficient solution approaches by using classical algorithmic and graph theory. The course emphasizes the importance of both digitalization and the relationship between algorithms and programming, as well as the aspects related to project management and problem solving skills by means of the development of a final coding project aimed at solving a specific problem assigned each year. The problem may arise potentially by any area of management engineering or computer science; it may enjoy potentially any routing, partitioning, coloring, location, telecommunication, sustainable logistics and supply chain management, portfolio, scheduling, data mining or business analytics features, and may have any general structure. The students will have to work in group to tackle and solve it in the most efficient way as well as to be ready to defend their work during the examination session.
The course includes in particular the following topics:
The course includes in particular the following topics:
- Algorithms and Algorithmic Analysis
- Induction, Recursion, and Search
- Fundation of data structures: Trees and Graphes
- Basic algorithms on graphs
- Brute-force search
- Introduction to complexity classes
- Well Solved Optimization Problems in Management Science - Part I: Spanning Trees
- Well Solved Optimization Problems in Management Science - Part II: Shortest Paths
- Hard Optimization Problems in Management Science - Part I - Spanning Trees with constraints
- Hard Optimization Problems in Management Science - Part I - Shortest Paths with constraints
Teaching methods
Interactive whiteboard lectures and exercises in the computer rooms.
Attending the course is strongly adviced and mandatory for the very first lecture.
Attending the course is strongly adviced and mandatory for the very first lecture.
Evaluation methods
The evaluation for this course is governed by Article 78 of the RGEE and follows a "unique" format. It involves both an evaluation in itinere and the development of one or more coding projects, with requirements and specifications potentially varying each year. The evaluation in itinere can contribute up to 55% of the final grade, while the project(s) may contribute up to 45%. These percentage are indicative and may be adjusted annually depending on the specifications of the projects. Full details, including any adjustments, are provided by the lecturer during the first mandatory class session.
Other information
The main language of this course is English.
Online resources
Please, refer to the slides of the course as well as to the official channel in Microsoft Teams.
Bibliography
Please, refer to the slides of the course.
Teaching materials
- All materials can be found in the official channel of course (Teams platform)
Faculty or entity
