Remy Spliet

Remy Spliet is an Associate Professor in the Department of Econometrics at Erasmus School of Economics, Erasmus University Rotterdam. His research lies at the intersection of operations research, logistics, and mathematical optimization, with a strong emphasis on real-world applications in transportation and supply chain systems.

His primary research interests include:

• Vehicle Routing Problems under uncertainty
• Stochastic demand modeling in logistics
• Dynamic time slot management for attended home delivery
• Inventory control strategies to reduce food waste
• Mathematical programming techniques such as column and row generation
• Integration of machine learning in operational decision-making

The most recent articles highlight a consistent trend in solving complex logistical challenges using advanced optimization and data-driven methods. His work often addresses scalability, computational efficiency, and practical feasibility in dynamic environments, particularly in last-mile delivery and retail operations. Collaborations with researchers like N. Agatz and T. Visser indicate an active research network in transportation science.

Remy Spliet has contributed to high-impact journals including Transportation Science, European Journal of Operational Research, and Omega. While no formal awards are listed in the provided text, his publications have accumulated citations and engagement across academic platforms.

He is actively involved in supervising academic work, with five supervised projects documented. His research is applied in nature, often targeting improvements in service efficiency, cost reduction, and sustainability in logistics and retail. He has also presented his findings at academic events, such as a 2017 oral presentation on a branch-and-cut algorithm for time window assignment in vehicle routing.

Remy Spliet is part of a vibrant research ecosystem at Erasmus School of Economics, contributing to both theoretical advances and practical implementations in operations research and econometrics.