Optimization and operations research
The research activities of the group concern the application of optimization models and methods in contexts ranging from production planning and financial optimization to prescriptive analytics in retail and marketing.
From the methodological point of view, the adopted tools include exact and approximate methods for combinatorial optimization. The latter methods do not consist only of classical local search strategies and metaheuristics, but also more refined matheuristics approaches that combine explicit mathematical models and intelligent search. Moreover, the group is active on the general theme of decision making under uncertainty. Themes include stochastic programming with recourse, robust optimization (both worst-case and under distributional ambiguity), dynamic programming, and simulation-based surrogate optimization.
- Applicazioni in ambito retail e marketing, e gestione della filiera logistica
- Ottimizzazione surrogata per il progetto e controllo di sistemi
- Programmazione dinamica approssimata e reinforcement learning
- Robust and stochastic optimization