Optimization Techniques

The goal of this course is to provide the fundamentals of numerical optimization. We will focus on various kinds of optimization techniques, ranging from continuous to discrete optimization methods, including global and local search methods, derivative-based and derivative-free algorithms, as well as traditional operational research techniques such as those used for solving integer programming, linear programming, and quadratic programming problems. We will address both theoretical and practical considerations, complementing each lecture on the theory with a dedicated lab. During the labs, the students will have the opportunity to test the various techniques on synthetic and real-world optimization problems.

At the end of this course, the students will be familiar with the fundamentals of numerical optimization, and will be able to apply various kinds of optimization algorithms to different contexts. They will also know the basic theory needed for developing new algorithms, or adapting/tuning them to handle new problems.

Material

All the course material is available (for UNITN students) on Moodle (course "Optimization Techniques [145865]").