Open Research Software and Data
Software and data are research outputs at IOLab. We develop reusable frameworks for implementing optimization algorithms and publish instances, validators, and experimental code so that results can be reproduced and extended.
Our main software projects include EasyLocal++, a C++ framework for local-search algorithms, and JuLES, its Julia counterpart. The group also maintains QuadProg++, a C++ implementation of the Goldfarb-Idnani quadratic-programming algorithm, and OptHub, a web platform for managing optimization instances and solutions.
Recent open datasets cover home healthcare routing and scheduling, periodic waste collection, electric-vehicle routing with nonlinear charging, oven scheduling, and educational timetabling. Source code and data are available through the IOLab GitHub organization.
Luca Di Gaspero
Associate Professor of Information Technology · Director of IOLab
Director of IOLab. He develops intelligent optimization methods and decision-support systems, from metaheuristics and hybrid algorithms to large language models.