Advancing Time Window Assignment and Vehicle Routing in Last-Mile Logistics

Abstract

We focus on how to make smart, reliable time window assignment under uncertainty, in ways that keep customers satisfied and keep operations efficient. We explore three closely related time window assignment practices, each reflecting how and when commitments are made: (i) next-day delivery with stochastic travel times, where windows must be promised before full uncertainty is revealed, (ii) dynamic next-day booking systems, where providers must decide when to communicate commitments, and (iii) same-day services, where customers select time slots in real time and the design of the slot menu directly influences both customer choices and operational feasibility. Service providers face multiple sources of uncertainty, including fluctuating demand, variable travel times, and dynamic booking patterns. Early commitments can improve customer experience but restrict routing flexibility, while delayed communication allows for more efficient planning but risks frustrating customers. We develop novel models and methodologies that integrate stochastic optimization, anticipatory decision-making, and machine learning. Together, these contributions provide a unified framework for balancing efficiency, reliability, and fairness in last-mile delivery systems, and they illustrate how optimization and learning can be combined to meet the growing demands of customer-centric logistics.

Biography

Sifa Celik graduated from her Bachelor’s study on Industrial Engineering at Bilkent University, Ankara where she pursued her master degree later on in 2019. In her master’s thesis, she focused on building exact algorithms for stochastic team orienteering problem. In 2021, she joined Operations Planning and Control group at the department of Industrial Engineering at Eindhoven University of Technology. Her research focuses on exact algorithms for stochastic routing problems, modelling dynamic time window assignment problems and developing machine learning algorithms for them. She will defend her thesis on March 2026.