5 papers
Trie Constraints and Hierarchy-Aware Semantic Alignment for HS Code Prediction with Small Language Models
Minseop Kim, Taekhyun Park, Kikun Park +1
Harmonized System (HS) code prediction (HSP) from commodity text is essential to international trade, and its importance continues to grow in port logistics. Recently, large langua…
Variable-Horizon Workforce Demand Forecasting with an Aggregate Demand Constraint for Construction Workforce Planning
Hanbyeol Park, Jaehyeon Heo, Taekhyun Park +2
Workforce planning is a recurring operational decision during construction projects that requires accurate forecasts of the future workforce demand for individual tasks. However, i…
Application of Large Language Models for Container Throughput Forecasting: Incorporating Contextual Information in Port Logistics
Minseop Kim, Jaeeun Kwon, Hanbyeol Park +3
Recent advancements in generative artificial intelligence (AI) have demonstrated its substantial potential in various fields. However, its application in port logistics remains und…
Generative AI and Machine Learning Collaboration for Container Dwell Time Prediction via Data Standardization
Minseop Kim, Takhyeong Kim, Taekhyun Park +2
Import container dwell time (ICDT) prediction is a key task for improving productivity in container terminals, as accurate predictions enable the reduction of container re-handling…
A Surrogate Model for Quay Crane Scheduling Problem
Kikun Park, Hyerim Bae
In ports, a variety of tasks are carried out, and scheduling these tasks is crucial due to its significant impact on productivity, making the generation of precise plans essential.…