讲座时间：10月28日14:30-16:30

讲座地点：交运楼418报告厅

主讲人简介：Andrea D’Ariano received the B.S. and M.S. degrees in computer science and automation engineering from Roma Tre University, and the Ph.D. degree in 2008, under the supervision of Prof. I.A. Hansen. In November 2003, he joined the TRAIL Research School and the Department of Transport and Planning, Faculty of Civil Engineering and Geosciences, Delft University of Technology. In 2018, he got the Full Professor Italian Scientific Habilitation in Operations Research. He served as an Expert for European Commission and numerous national research foundations. He is currently an Associate Professor with the Department of Engineering, Roma Tre University. He is currently coordinating the AIRO Chapter on Optimization in Public Transport and Shared Mobility. His research publications were acknowledged by TRAIL, IAROR, INFORMS RAS, and AGIFORS as best papers, and by the IEEE ITSS as the best Ph.D. dissertation. His main research interest includes the study of scheduling problems with application to public transportation. He is also an Associate Editor of well-known international journals (e.g., Transportation Research Part B) and conferences (e.g., IEEE ITSC).

讲座内容简介：This talks reports on a state-of-the-art train rescheduling solver and potential practical applications. The final goal is the development of an advanced decision support system for supporting dispatchers work and for guiding them toward near-optimal real-time train re-timing, re-ordering and re-routing decisions. The talk focuses on the optimization system AGLIBRARY that manages trains at the microscopic level of block sections, block signals and at a precision of seconds. The system is based on generalized job shop scheduling (alternative graph) formulation of the train rescheduling problem and on customized exact and (meta)heuristic solution methods (from greedy heuristics to advanced variable neighborhood and tabu search algorithms). The system outcome is a detailed conflict-free train schedule, being able to avoid deadlocks and to minimize the propagation of train delays in the railway network.Experiments on Dutch and British railway networks demonstrate that AGLIBRARY can quickly compute near-optimal solutions.