Computational OPTIMIzATION

RESEARCH GROUP @ UNIPV

We are a group of researchers working on challenging Mathematical Optimization problems using numerical methods based on Mathematical Programming, Machine Learning, and Artificial Intelligence.

We love to put optimization theory into practice while solving industrial applications.

We are passionate about new theoretical questions coming from real-life applications.

RESEARCH TOPICS

Computational Optimal Transport

Model and Algorithms for Kantorovich-Wasserstein distances, Wasserstein Barycenters, and Fourier-based metrics

Healthcare Management

Models and algorithms to deal with challenges arising from health service management and to support decisions under uncertainty

Combinatorial Optimization

Traveling Salesman Problem, Graph Coloring, Stable Set, Total Matching, and Total Coloring

Interpretable Machine Learning

Development of Machine Learning techniques based on interpretable mathematical models that provide explainable outcomes

Multimodal Routing

Joint Project with EU-JRC, Seville: Development of VelociRaptor, a parallel schedule-based multimodal routing solver, customized for all-pairs shortest path queries

Robust Optimal Power Flow

Development of models and algorithms regarding the Optimal Power Flow problem in a stochastic setting that arises from Renewable Energy Sources