Order batching problems in parallel-aisle order picking systems with larger-than-bin orders
New paper has been published in Journal of the Operational Research Society.
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 Journal of the Operational Research Society.
SimPL lab’s undergraduate students won Smart logistics service innovation idea contest.
Siemens posts our achievements about KSS student competition and research publication.
Taehoon Lee and Bonggwon Kang gave presentations at the KIIE Fall Conference 2023