CODING PROJECT

Teacher(s)

Catanzaro Daniele;

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.   

Aims

At the end of this learning unit, the student is able to :
1	This course contributes to develop the following competencies. Knowledge Scientific reasoning and systematic approach Project management Leadership At the end of this course, students will: Improve their strategical thinking skills Acquire fundamental knowledge on the modeling and the resolution of practical problems Apply the appropriate techniques to propose a useful solution.

Content

This course provides an introduction to algorithmic problem solving. Its main goal is to learn how to implement solution approaches for different type of problems involving search and optimization features. It covers the introduction to graph theory, classical algorithms on graphs, algorithmic paradigms, and data structures used to solve these problems. The course emphasizes the relationship between algorithms and programming. It pays attention on the practical importance of specific classes of optimization problems in management science and motivate the students to develop algorithms to solve them.
The course includes in particular the following topics:

1. Recursion
2. Fundation of data structures: Graphes
3. Basic algorithms on graphs
4. Well Solved Optimization Problems in Management Science - Part I: Spanning Trees
5. Well Solved Optimization Problems in Management Science - Part II: Shortest Paths
6. Hard Optimization Problems in Management Science - Part I - Spanning Trees with constraints 
7. Hard Optimization Problems in Management Science - Part I - Shortest Paths with constraints 
8. Finding the optimum via Branch-&-Bound
9. Introduction to Heuristics, Local Searches and Metaheuristics

Teaching methods

Due to the COVID-19 crisis, the information in this section is particularly likely to change.

Standard blackboard lectures. Attending the course is strongly adviced and mandatory for the very first lecture.

Evaluation methods

Due to the COVID-19 crisis, the information in this section is particularly likely to change.

Continuous evaluation, with quizzes in itinere and a final project.The topic of the project may change from year to year; its statement as well as the specific modalities of its discussion will be defined during the very first lecture of the course. 

Other information

The main language of this course is English. 

Online resources

Please, refer to the slides of the course.

Bibliography

Please, refer to the slides of the course. 

Teaching materials

• Please refer to the Teams platform

Faculty or entity

CLSM