Prof. Andrea D'Ariano, Roma Tre University, Italy

Andrea D'Ariano is Full Professor at Roma Tre University, Department of Civil, Computer Science and Aeronautical Technologies Engineering. He got the Italian Full Professor Scientific Habilitation in Operations Research and Transportation Science. His research publications were acknowledged by Industrial Engineering and Operations Management (IEOM) Society as Outstanding Professor Award; Airline Group of the International Federation of Operational Research Societies (AGIFORS), INFORMS Aviation Applications Section, INFORMS Railway Applications Section, International Association of Railway Operations Research (IAROR), Netherlands Research School on Transport, Infrastructure and Logistics (TRAIL) as best scientific papers; by IEEE Intelligent Transportation Systems Society as best PhD thesis; by Italian Operations Research Society (AIRO) as best Master thesis. He has published more than 250 peer-reviewed international publications (including top-cited papers in high-impact journals). He served as Editor and/or Reviewer for international journals and as External Expert and Rapporteur for European Commission and numerous National Foundations. Andrea D’Ariano is listed in the 2023 ranking of the top 2% of the world’s best scientists, compiled by Stanford University, DOI:10.17632/btchxktzyw.6

Keynote Speech: Train scheduling optimization with consideration of passenger flows during disturbed operations

Abstract: Optimization models for railway traffic management tackle the problem of determining, in real-time, control actions to reduce the effect of disturbances. Two main research streams can be identified. On the one hand, train scheduling models are designed to include all conditions relevant to achieve feasible and efficient operation of rail services, keeping as much as possible train punctuality. On the other hand, delay management models focus on the impact of rescheduling decisions on the quality of service perceived by passengers. The resulting objectives are conflicting whenever train delay reduction requires cancellation of some connected services, causing extra waiting times to transferring passengers. The infrastructure manager and the train operating companies need to discuss on which connections to keep or drop.
This talk investigates hybrid railway traffic optimization approaches, merging these two streams of research. First, we consider the bi-objective problem of minimizing train delays and missed connections to provide a set of feasible non-dominated schedules, supporting the decisional process. We use a detailed alternative graph model to ensure schedule feasibility and develop heuristic algorithms to compute the Pareto front of non-dominated schedules. Second, we introduce a comprehensive mathematical model, incorporating the traffic regulations and the passenger rerouting options at a microscopic level. Third, we study this problem as a game theoretical approach, focusing on the solutions corresponding to Nash equilibria of a game involving passengers and infrastructure managers. Computational results based on a conventional Dutch railway network quantify the trade-off between the minimization of train delays and passenger travel times.

Prof. Tien Fang Fwa, National University of Singapore, Singapore

Dr. T. F. Fwa is currently an emeritus professor in the Department of Civil & Environmental Engineering, National University of Singapore (NUS). He is also a Distinguished Professor at Chang’an University in China, where he serves as the Dean of the School of Future Transportation. He is a Fellow of the Academy of Engineering, Singapore. Dr. Fwa’s main research effort has been focusing on transportation infrastructure performance evaluation and management. He is the Joint Editor-in-Chief of the Journal of Road Engineering. He also serves on the editorial boards of six other leading pavement engineering journals. He has published more than 200 technical papers in leading international journals, and has been invited to lecture in more than 20 countries. Dr. Fwa was the founding President of the Pavement Engineering Society (Singapore), and the Asia Pavement Engineering Society (APES). He was the President of the International Society for Maintenance and Rehabilitation of Transport Infrastructure (iSMARTi) from 2012 to 2016. He founded two international conference series, namely the International Conference on Road and Airfield Pavement Technology (ICPT), and the Asia Pacific Symposium on Transportation and the Environment (APTE).

Keynote Speech: Roles of Transportation Infrastructure in Logistics

Abstract: Transportation infrastructure is the physical backbone of global supply chains, facilitating the movement of raw materials to production sites and the delivery of finished goods to end consumers. Its performance is multifaceted and critically shapes the efficiency, reliability, and overall competitiveness of logistics networks. This presentation will analyze how the performance of key infrastructure components -- terminals, links, and carriers -- directly impacts logistics costs, operational efficiency, and safety. A primary focus will be placed on the transformative role of Artificial Intelligence (AI) in transportation logistics. The significant benefits arising from the deep integration of AI into these systems will be examined. The presentation will be illustrated with case studies showcasing successful AI implementations across various transportation sectors, highlighting practical pathways to enhanced performance.

Prof. Toshiyuki Yamamoto, Nagoya University, Japan

Toshiyuki Yamamoto is Professor of Transportation Planning and Vice Director of Institute of Materials and Systems for Sustainability at Nagoya University, Japan. Prior to Nagoya University, he served as Research Associate at Kyoto University, Japan, where he obtained Doctor of Engineering in 2000. His research interests are next-generation mobility, activity-travel behavior, traffic safety, etc. He is Principal Investigator of the project, Optimization of carbon emission management policy and low-carbon travel induction strategies for demand-responsive transportation systems, bilaterally funded by NSFC and JSPS. He serves as Associate Editor for the journal, Transportation, and International Steering Committee Member for International Conference on Transport Survey Method.

Keynote Speech: Door-to-door personal rapid transit system: concept and simulation

Abstract: Insufficient accessibility to public transit is one of the significant barriers to prevent transit usage. Especially, in super aging society including Japan, the distance to train/subway stations and bus stops is more important than ever. First- and last-mile service is preferred, but sometimes infeasible. Also, even if feasible, the transfer at the station significantly deteriorates the service level compared to private car. We introduce an innovative mobility service model that combines Personal Rapid Transit (PRT) technology with low-speed autonomous vehicles to enhance mobility and improve first- and last-mile connectivity through on-demand, door-to-door services. The analysis explored various configurations for PRT-dedicated lanes and tested different signal timing strategies. The findings highlight an optimal integration plan that ensures efficient PRT operations while minimizing disruptions to overall traffic flow. By aligning infrastructure design and signal control with the specific requirements of emerging mobility systems, this study addresses practical implementation challenges and provides actionable insights for deploying innovative mobility services.

Prof. Wai Yuen SZETO, The University of Hong Kong, China

Prof. Wai Yuen Szeto is a Professor and an Associate Head at the Department of Civil Engineering at The University of Hong Kong, and the Director of the Institute of Transport Studies at that university. He is a Top 0.05% Transport Scholar in 2024 and 2025 by ScholarGPS, a Top 1 % Scholar during 2015-2025 (according to Clarivate Analytics’ Essential Science Indicators), and currently a World’s Top 2% Scientist by Stanford University. His current h-index is 68 (Google Scholar). He is an author of over 170 refereed journal papers, with two papers in Operations Research and 35 papers in Transportation Research Part B. His publications have been cited over 15000 times (Google Scholar). The publications are related to shared mobility, smart sustainable transport, dynamic traffic assignment, transport network design, public transport, and transport network reliability. Currently, he is an Editor-in-Chief of Transportmetrica B, an Associate Editor of Transportation Research Part E, Journal of Intelligent Transportation Systems, an Area Editor of Networks and Spatial Economics, and an Editorial Board Member of Transportmetrica A, Travel Behaviour and Society, Transportation Research Part C, and International Journal of Sustainable Transportation.

Keynote Speech: A multi-period asymmetric transit frequency design problem

Abstract: Transit frequency design is critical in determining the performance of public transit services. In the literature, single-period frequency design is often considered but ignores the demand variation over time of day. Moreover, in high-demand bus networks, the demand patterns are asymmetric in both directions of some bus routes. This study investigates a bus operation strategy to address these two issues. In this strategy, for each route, a class of buses serves both directions while the other class only serves one direction with high travel demand, leading to the two directions having different frequencies. A bilevel optimization problem is formulated for this strategy. The upper level problem is a multi-period asymmetric transit frequency design problem, which aims to determine the route frequencies of different classes of buses associated with each period to maximize the operating profit or social welfare. This upper level problem also considers deadhead trips between the bus depot and terminals or between terminals of different routes across periods. The lower level problem is a schedule-based user equilibrium transit assignment problem, taking elastic demand, the common line choice of passengers, and capacity constraints into account. A hybrid algorithm combining an enhanced artificial bee colony algorithm with the method of successive averages is proposed to tackle the bilevel optimization problem and then applied to the study of the Tin Shui Wai bus network to demonstrate the model properties. The effectiveness of the proposed algorithm is also examined. The results indicate that the proposed algorithm can produce better solutions compared with the modified hybrid genetic algorithm. Moreover, the proposed multi-period asymmetric design outperforms the existing design, which can achieve less passenger travel time and greater demand satisfaction, operating profit, and social welfare.