Applied Computer Science and Artificial Intelligence

PAUL JOSEPH WOLLAN

General goals:
Introduction to mathematical modelization of optimization problems, Linear and Integer programming and their applications in real contexts.

Specific goals:
To learn:
1. Main problem modelling techniques using mathematical and logical language
2. Main theory properties and their practical applications for optimization problems
3. Linear programming and simplex algorithm and its applications.
4. Competences for software for modelling and optimization

Knowledge and understanding:
develop
1. the ability of conciseness, of logical reasoning and problem solving trhough quantitative models;
2. the ability to describe and solve e risolvere (also at high level) computationally hard problems;
3. the ability to use english written bibliography and software;
4. the ability to identify precisely optimization problems and when they are linear integer or non-linear;
5. the ability to design a implementable version of mathematical optimization problem model and finding solution
for the model using appropriate algorithms. Interpreting the solutions.


Applying knowledge and understanding:
1. Real applications of optimization problems (especially on networks)
2. Skills on using software for modelling and optimization

Critical and judgmental skills:
Enabling autonomous thinking in the student by deepening the ability of mathematical reasoning of the student through the development of logical language and problem solving abilities.

Communication skills:
Group work aimed at solving optimization problems drawn from everyday cases, develop communication abilities in explaining and focusing optimization problems on concrete working examples

Learning ability:
Skills and theoretical tools acquired during the course are basic for more advanced courses on topics concerning computational complexity, network algorithms, graph theory.