Transforming Freight Logistics and Transportation by Optimization and Data-Driven Methods

Francesco Carrabs is a full professor of Operations Research at the University of Salerno. His research focuses on exact and heuristic methods for optimization problems on graphs, including routing, spanning trees, and wireless sensor networks. He is also the principal investigator of the PRIN PNRR 2022 project "Smart Agriculture by Collaborative Robots Swarm (SmaCRoS)." Raffaele Cerulli is a full professor of Operations Research and the Head of the Mathematics Department at the University of Salerno. Furthermore, he is the president of AIRO, the Italian Association of Operations Research. His research covers combinatorial optimization, network flow, sensor networks, and meta-heuristic algorithms. He has authored 90 refereed papers. Moreover, he leads research projects funded by the Italian Ministry of University and Research and the Ministry of Economic Development. He is also the Editor-in-Chief of Soft Computing (Springer). Francesca Guerriero is a full professor of Operations Research at the University of Calabria. She served as the Dean of the Department of Mechanical, Energy and Management Engineering (DIMEG) at the same university from 2021 to 2025. Her research focuses on network optimization, logistics, revenue management, and quantum computing. She has led several national and international research projects, including the PRIN 2022 “Optimizing Sustainable Multi-modal and Multi-tasking Last-mile Distribution System with Carbon-free Autonomous Vehicles, Ground Robots, Drones, and Public Transport (SMOTION)” and the PRIN PNRR 2022 “Smart Agriculture by Collaborative Robots Swarm (SmaCRoS)”, funded by the Italian Ministry of University and Research. Marcella Samà is an associate professor in Operations Research at the Roma Tre University. She is involved in developing models and algorithms for scheduling and public transit optimization. She also coordinates the PRIN PNRR project "Co-Opetitive Sustainable Mobility Optimization (COSMO)" and is active in AIRO, EURO, and INFORMS, contributing to research on shared mobility, logistics, and public transportation systems. Claudio Sterle is an associate professor in Operations Research at the University of Naples Federico II. His research activity focuses on combinatorial and network optimization, with particular emphasis on logistics and last-mile delivery. He is the principal investigator of the PRIN 2022 project EcosustAinable effiCient tecH-drIven Last miLE logiStics (ACHILLES) and has also contributed to the research activities of MOST, the Italian National Center for Sustainable Mobility funded under the PNRR, supporting work on innovation and optimization in logistics and transport systems.

• Part I. Sustainable Approaches to Urban Freight and City Planning.- Chapter 1. Integrating ADRs with Public Transit for Sustainable Logistics: A Case Study in Naples.- Chapter 2. The Vehicle Routing Problem with Autonomous Delivery Robots and Public Transit.- Chapter 3. Optimizing Parcel Locker Networks: Case Studies in Naples and Catani.- Chapter 4. Urban Green Area Planning in Multi-City Environments.- Part II. Optimizing AGV and UAV Systems for Civil Use.- Chapter 5. Truck–Drone Delivery in Practice: A Local Search Metaheuristic with a Real-World Pharmaceutical Case Study.- Chapter 6. A close-enough event-driven approach for the dynamic assignment of targets to a fleet of autonomous vehicles.- Chapter 7. A MILP-based Heuristic Approach for the Multiple Close-Enough Traveling Salesman Problem.- Part III. Automated and Sustainable Warehouses.- Chapter 8. A dynamic programming algorithm for an order picking problem with deadlines.- Chapter 9. A mixed-integer linear program and a carousel greedy algorithm for the scheduling of pick-up and delivery operations in automated warehouses.- Chapter 10. Low-Carbon Warehouse Scheduling via GRASP Optimization.- Part IV. Leveraging Data and Optimization for Added Value.- Chapter 11. A Lagrangean-Based Cut for a Branch-and-Cut Approach to the Resource-Constrained Covering Tour Problem.- Chapter 12. Semisupervised classification for active learning.