A course on optimization models and numerical methods taught by Professor Bemporad.
From December 1 to 5, the IMT School will offer the course Numerical Optimization, taught by Professor Alberto Bemporad, Professor of Control Systems.
Optimization plays a key role in addressing decision-making problems across engineering, data science, machine learning, business analytics, finance, and economics. The course introduces participants to optimization modeling and to the most widely used numerical methods for solving complex problems.
Syllabus (short overview)
Topics include linear and convex optimization models; optimality conditions, sensitivity, and duality; algorithms for constrained convex optimization such as active-set and quadratic programming methods, proximal methods and ADMM, stochastic gradient, interior-point methods; and nonlinear optimization techniques including line-search methods and sequential quadratic programming.
Prerequisites
Knowledge of linear algebra, matrix computation, calculus, and mathematical analysis.
Timetable
December 1–5, 2026
Daily sessions: 09:00–11:00 and 14:00–18:00
For further information please contact:career.service@imtlucca.it
