Projects

QLMD: Quantum Computing for Efficient Urban Logistical Ecosystem

Quantum computing for solving urban logistics criticality

Funding: ICSC Innovation Funds

Enabling technology: Big Data Analytics, Geographic Information Systems (GIS), Quantum computing

Sustainable Development Goals

Quantum computing will serve to revolutionize urban logistics services, including waste collection and delivery systems, by optimizing their routes. It will also enable improved predictive analysis and efficient management of delivery schedules, urban restrictions, and circulation regulations. The project aims to improve urban sustainability (reducing traffic, emissions, and waste) and increase operational efficiency.

National Centre for HPC, Big Data and Quantum Computing (ICSC), a project funded by the European Union – NextGenerationEU – and by Italy’s National Recovery and Resilience Plan (PNRR) – Mission 4, Component 2.

Objectives

Quantum computing offers an innovative solution to the complex challenges of urban logistics problems, including waste collection and last-mile delivery, addressing problems such as the Traveling Salesman Problem and the Vehicle Routing Problem. This will make it possible to minimize operational costs, such as time, distance, traffic congestion, and fuel consumption, despite various logistics constraints.

Initial challenge

The project addresses a varied and complex problem, due to the variety of routes, diversification of production, and operational constraints. It also keeps in mind the growing need to respect environmental sustainability and achieve customer satisfaction. Quantum computing is a resource capable of easily processing this large amount of data, optimizing results based on customer needs, and evaluating multiple potential solutions simultaneously.

Solution

The result will lead to optimization of urban logistics systems: thanks to improved predictive analysis algorithms made possible by quantum computing, it will be possible to reduce waste and emissions while ensuring greater sustainability for these systems.

Benefits

The efficiency of logistics ecosystems will translate into greater efficiency and reduced operational costs. Furthermore, the project aims to minimize logistics-related risks, resulting in increased economic activity and improved quality of life. This will occur with a view to reducing carbon emissions and fuel consumption by identifying optimized routes.

IFAB’s role

IFAB contributed to the development and integration of quantum computing methodologies and optimization tools needed to address one of the classic urban logistics problems: optimal delivery route planning, formalized as the Traveling Salesman Problem (TSP).

IFAB’s technical contribution was organized on four fronts:

Implementation of a quantum solver for the TSP based on the QAOA algorithm, with problem formulation as a QUBO model capable of incorporating real operational constraints — vehicle capacity, road accessibility, time windows.
Integration of the solver with CINECA’s Leonardo supercomputer, for efficient simulation of quantum instances on high-performance computing infrastructure.
Development of a hybrid pipeline combining hierarchical agglomerative clustering techniques with quantum optimization, to make the system scalable for large-scale instances.
Validation of solutions on synthetic datasets and scenarios inspired by the Milan metropolitan network, with systematic benchmarking against classical metaheuristics.

Participation in QLMD made it possible to consolidate advanced expertise in Quantum Computing applied to combinatorial optimization, helping to advance the technology from TRL 3 to TRL 5 and translating results into peer-reviewed scientific publications, including a contribution to the AIxQIA workshop at ECAI 2025 and a paper on arXiv.