Bayesian Optimization for Weight-based Dispatching of Stocker Systems in a Display Fab
New paper has been published in Korean Society of Industrial and Systems Engineering
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
New paper has been published in Korean Society of Industrial and Systems Engineering
Our students won the Grand Prize at the 2026 KSIE Undergraduate Project Competition.
Our students received an award at the 2026 Spring Conference of the Korean Society of Industrial and Systems Engineering.
Our students received an award at the 2026 Korea Logistics Society Spring Conference.