Simulation-based Optimization of Railway Seat Capacity Allocation Considering Passengers’ Seat Selection
A new paper has been published in the Korean Journal of Logistics.
Our simulation models investigate the production logistics.
Our machine learning applications optimize them.
The objective of the Simulation & Production Logistics (SimPL) Laboratory is to develop large-scale simulation models, operational algorithms, machine learning models that will improve the operations and productivity of logistics and related production systems. Active research areas include simulation optimization, material handling and self-organizing operations, and OR applications in warehousing, semiconductor, display, and automobile industries.
Business areas: Material handling and production logistics in distribution centers, container terminals, semiconductor and display fabs, and construction equipment assembly line
OR approaches: Large-scale simulations, machine learning models, and optimization models
Operational strategy: Simulation optimization, self-organizing/-balancing operations
A new paper has been published in the Korean Journal of Logistics.
SIMPL Lab is looking for new members to join our team.
New paper has been published in Simulation Modelling Practice and Theory
Samsung Display & SimPL Lab 7th Joint Workshop was held at PNU on August 19–20, 2026.