Alberto Santini, CY Cergy Paris Université

Alberto Santini, PhD

Alberto Santini founded AIROYoung, the youth chapter of the Italian Operational Research Society (AIRO), and EUROYoung, a Forum within the Association of European Operational Research Societies. He also served as an elected member on the board of directors of AIRO.

He has been a Principal Investigator for a Planetary Wellbeing grant (to study the optimization of indoor farms) and a BGSE Seed Grant (to increase the sustainability of last-mile supply chains). He was also awarded scholarships by the Spanish government (Juan de la Cierva grant) and a "best paper" award by the journal Omega.

His main research area is combinatorial optimization, including both exact and heuristic methods. His academic interests span from logistics and production planning, to problems on graphs and the methodological aspects of meta-heuristics. His papers and source code are available at https://santini.in/.

Hi is also a Marie Sklodowska-Curie Fellow in the EUTOPIA-SF action.

The boom of e-commerce in the last decade (and its growth projections for the coming years) raises new challenges as retailers and couriers innovate their supply chains to keep up with demand. Last-mile delivery (LMD), the segment of the supply chain which starts at the last distribution centre and ends at the customer’s doorstep, is particularly affected. Its nature changed when retailers stopped delivering to stores and started delivering directly to consumers: couriers now handle a large number of small parcels, instead of fewer, larger shipments; they deliver during tight time windows, when customers are at home; they deal in real-time with newly incoming orders while their fleet is already busy shipping other parcels.

Retailers need decision support tools to run their LMD segments smoothly, and the Operational Research (OR) community has responded to the challenge, proposing models and algorithms to optimize LMD operations. There are, however, important open issues that have not been considered in these models, but which must be tackled timely to guarantee the feasibility of this business in the next decades, especially in dense urban environments.

The main open issue is the sustainability of current last-mile operations with ever-higher demand. There is only a limited number of delivery vans which our cities can absorb before the externalities (traffic, emissions) become too large to bear.

This proposal urges to integrate traditional LMD operations (e.g., transport vans) and new technologies (e.g., porters and the crowd) in a framework which: 1. is compatible with the highly dynamic nature of modern e-commerce; 2. synchronizes multiple actors (vans, porters, the crowd); 3. explicitly accounts for the environmental sustainability of operations under increasing demand, specifying hard limits on emissions and traffic generated by LMD operations. The literature suggests that some of these points can be separately included in OR models. This proposal aims at tackling them jointly, combining interdisciplinary tools from OR, machine learning, and economics.