Speaker: Dr Lele (Joyce) Zhang – (Optima/Melbourne University)

Bio:

Dr Lele (Joyce) Zhang is an Associate Professor in School of Mathematics and Statistics at the University of Melbourne (UoM). She has a Bachelors Degree in Engineering (Southeast University, China), and a PhD in Operations Research (UoM). Her areas of expertise are broadly modelling and optimisation for complex systems, traffic flow theory, Monte Carlo simulation, scheduling theory, City Logistics, and automated optimisation using large language models and machine learning. She was an Associated Investigator of ARC Centre of Excellence for Mathematical and Statistical Frontiers (ACEMS), and is a Chief Investigator of ARC Training Centre in Optimisation Technologies, Integrated Methodologies, and Applications (OPTIMA) and a co-founder of Physical Internet Lab at UoM. She also has extensive collaborations with industries in logistics, transport, and healthcare, including Australia Post, Department of Transport (Victoria), and Australian Red Cross Lifeblood. Her work has received several awards, including the second prize of Social Science Research Excellence Award by Lanzhou Province, China, the best poster and paper awards from International Physical Internet Conference (2025), and the best conference paper and presentation from International Symposium of Multimodal Transportation (2024).

Abstract:

Last-mile parcel delivery illustrates a difficult logistics challenge: decisions about when and where to deliver interact with vehicle routes, capacity, service commitments and customer preferences. The classical vehicle routing problem (VRP) helps delivery operators consolidate spatially by serving nearby customers together, but parcels for the same recipient may arrive at different times, creating opportunities for temporal consolidation. This talk develops that opportunity from deterministic planning to uncertain demand and customer choice. First, a two-echelon VRP formulation lets the operator jointly choose parcel schedules, home or locker delivery, and routes within delivery deadlines. The proposed bi-objective model captures the trade-off between operating cost and service satisfaction, while a three-phase heuristic tackles the integrated problem. Experiments on a Melbourne network show when holding parcels reduces repeat trips, particularly when travel is costly or customers are dispersed. Yet operators cannot simply change delivery times or locations, and parcel demand is uncertain when plans are made. A distributionally robust bilevel model therefore links operator incentives to customers’ utility-based choices; a tractable reformulation and three-level matheuristic connect those choices to routing and capacity. Computational results identify when deferral and mode switching complement each other, and how planning for uncertainty improves capacity reliability without excessive conservatism. These developments illustrate how optimisation can support more realistic logistics decisions.

This event is Hybrid:
JOIN VIA ZOOM – MEETING ID: 873 1557 5255; PASSWORD: 778635
Level 8, Room 8109, Melbourne Connect

SEMINAR: WED 21 OCTOBER 2026 4.00PM-5.00PM (AEST, Melbourne Time)