Vincenzo AULETTA | OPTIMIZATION TECHNIQUES FOR ENGINEERS
Vincenzo AULETTA OPTIMIZATION TECHNIQUES FOR ENGINEERS
cod. 8860500003
OPTIMIZATION TECHNIQUES FOR ENGINEERS
| 8860500003 | |
| DEPARTMENT OF INFORMATION AND ELECTRICAL ENGINEERING AND APPLIED MATHEMATICS | |
| Corso di Dottorato (D.M.226/2021) | |
| INFORMATION ENGINEERING | |
| 2024/2025 |
| OBBLIGATORIO | |
| YEAR OF COURSE 1 | |
| YEAR OF DIDACTIC SYSTEM 2024 | |
| SPRING SEMESTER |
| SSD | CFU | HOURS | ACTIVITY | |
|---|---|---|---|---|
| MAT/09 | 3 | 18 | LESSONS |
| Objectives | |
|---|---|
| To be able to model real world problems as mathematical optimization problems and incorporate uncertainty. To be able to implement optimization solvers. To be able to convert problems to their dual formulation. To be able to prove basic results on convex optimization. |
| Prerequisites | |
|---|---|
| The activity requires the previous knowledge of Calculus, Linear Algebra, Algorithm Design, and basics of Probability Theory. |
| Contents | |
|---|---|
| Convex Optimization Basics (Lectures: 3 hours) Duality Theory (Lectures: 3 hours) Gradient Descent Algorithms (Lectures: 3 hours) Algorithms for Linear Programming: Simplex and Interior Points Method (Lectures: 3 hours) Cutting Planes Methods (Lectures: 3 hours) Integer Programming (Lectures: 3 hours) |
| Teaching Methods | |
|---|---|
| The course includes 18 hours of lectures. Lectures are aimed at acquiring knowledge about the basics of Convex Optimization and Duality Theory, and about the main known algorithms known for solving Convex Optimization Problems, and the special cases of Linear Optimization Problems and Integer Linear Optimization Problems. We will also provide many examples of application of optimization techniques to real problems in many different settings. Attendance to the lectures is mandatory; in order to be admitted to the exam, the student must participate to at least 70% of the hours. |
| Verification of learning | |
|---|---|
| The exam consists in an oral interview. The oral interview has an approximate duration of 30 minutes, and includes the discussion of an advanced topic related to course arguments, aimed at verifying the student’s ability to extract the main features of a concept or an algorithm and to apply them on a slightly different setting. The oral interview will also verify the theoretical knowledge of the course’s topics. |
| Texts | |
|---|---|
| References [1] S. Boyd and L. Vandenberghe - Convex Optimization [2] N. K. Vishnoi - Algorithms for Convex Optimization [3] B. Guenin, J. Konemann, L. Tuncel - A Gentle Introduction to Optimization [4] L. A. Wolsey - Integer Programming |
BETA VERSION Data source ESSE3 [Ultima Sincronizzazione: 2024-12-13]
