The research project aims to develop a software-based system capable of supporting institutions or companies in making fast and accurate decisions in sustainability-related scenarios, such as optimal route planning or risk mitigation plans.
After identifying a concrete case study, we will integrate: (i) real-world data sourced from publicly available datasets, (ii) artificial intelligence methods that learn from this data and dynamically refine scenario models, and (iii) advanced optimization algorithms that deliver effective and actionable solutions for decision makers.
In particular, we will focus on the Vehicle Routing Problem (VRP) family, a well-established and widely studied class of problems in the scientific literature, which provides a powerful framework for modeling key real-world challenges from a sustainability perspective.
Among the classes of algorithms, we intend to employ both traditional techniques and innovative quantum-based approaches, the latter being one of the most actively researched areas in recent years, with the potential to revolutionize not only computer science but also its application to real-world problems.
All outputs of the system will be evaluated and guided according to environmental criteria to ensure that proposed solutions contribute concretely to the reduction of ecological impact and are in line with the Sustainable Development Goals (SDGs) of the United Nations.