Papers

Research

Papers

Published work and manuscripts currently under review.

Under Review

Under Review
Learning a Unified Production and Charging Policy with Heterogeneous AGV Fleets in Manufacturing Systems
Seungkyu Yoon, Inguk Choi, and Hyun-Jung Kim
Under Review
Learning Generalizable Multi-Robot Scheduling from Local Observation in Conveyor-Based Robotic Workcells
Dong-Ha Lee, Inguk Choi, Yuqian Lu, and Hyun-Jung Kim
Under Review
Multi-Objective Photolithography Scheduling with Dual-Resource Constraints Using Graph-Based Reinforcement Learning
Sang-Hyun Cho, Inguk Choi, Boyoon Choi, Paul Han, and Hyun-Jung Kim

Publications

Journal Articles

EJOR
A Unified Learning Framework for the Block Relocation Problem: A New Performance Baseline
Woo-Jin Shin, Ji-Kang Jung, Sang-Hyun Cho, Inguk Choi, Shunji Tanaka, and Hyun-Jung Kim
European Journal of Operational Research (EJOR), 2026. (SCIE, Q1)
Paper
TR-C
Learning to Retrieve Containers: A Scale-Diverse Deep Reinforcement Learning Approach for the Container Retrieval Problem
Woo-Jin Shin, Inguk Choi, Sang-Hyun Cho, and Hyun-Jung Kim
Transportation Research Part C: Emerging Technologies (TR-C), vol. 183, article 105496, 2026. (SCIE, Q1)
Paper
IEEE RA-L
A Multi-View Attention-Based Encoder-Decoder Framework for Clustered Traveling Salesman Problem
Jimin Park†, Inguk Choi†, and Hyun-Jung Kim
IEEE Robotics and Automation Letters (IEEE RA-L), vol. 11, no. 1, pp. 137–144, 2026. (SCIE, Q1)
†: Co-first authors
Paper

AI/ML Conference Proceedings

NeurIPS 2026
Towards a Unified Model for Flexible Job Shop Scheduling with Diverse Constraints
Inguk Choi, Woo-Jin Shin, Sang-Hyun Cho, and Hyun-Jung Kim
Advances in Neural Information Processing Systems (NeurIPS), Sydney, Australia, 2026. (A* Conference)
Accepted
NeurIPS 2026
SchedDiff: Diffusion-Based Priority Refinement for Job Shop Scheduling
Dong-Yoon Oh, Sang-Hyun Cho, Inguk Choi, and Hyun-Jung Kim
Advances in Neural Information Processing Systems (NeurIPS), Sydney, Australia, 2026. (A* Conference)
Accepted
IJCAI 2026
Preference-Guided Multi-Policy Optimization for Flexible Job Shop Scheduling
Inguk Choi, Woo-Jin Shin, Sang-Hyun Cho, and Hyun-Jung Kim
Proceedings of the Thirty-Fifth International Joint Conference on Artificial Intelligence (IJCAI), pp. 6156–6165, 2026. (A* Conference)
Paper
NeurIPS 2025
Towards Generalizable Multi-Policy Optimization with Self-Evolution for Job Scheduling
Inguk Choi, Woo-Jin Shin, Sang-Hyun Cho, and Hyun-Jung Kim
Advances in Neural Information Processing Systems (NeurIPS), vol. 38, pp. 24569–24616, 2025. (A* Conference)
Paper

Conference Presentations

International

APIEMS 2026
A Generalizable DRL Scheduler for the Job Shop Scheduling Problem with AGVs
S. Lee, I. Choi, and H.-J. Kim
Asia-Pacific Industrial Engineering and Management Systems Conference (APIEMS), Busan, Korea, 2026.
Accepted
WSC 2026
RAG-enhanced Query Disambiguation in Spreadsheet-based Semiconductor Supply Chain Management
J. Park, I. Choi, S. Joo, Y. Kim, G. Oh, Y. Song, and H.-J. Kim
Winter Simulation Conference (WSC), Glasgow, Scotland, 2026.
Collaboration with Samsung Electronics
Accepted
CASE 2026
Real-Time Robotic Assembly Cell Scheduling via Generalizable Multi-Agent Reinforcement Learning
D.-H. Lee, I. Choi, W.-J. Shin, Y. Lu, and H.-J. Kim
IEEE International Conference on Automation Science and Engineering (IEEE CASE), Shenyang, China, 2026.
Collaboration with University of Auckland
WSC 2025
Learning-based Scheduling for Stochastic Job Shop Scheduling with Mobile Robots
W.-J. Shin, D. Oh, I. Choi, M. Wiktorsson, E. Florest-Garcia, Y. Jeong, and H.-J. Kim
Winter Simulation Conference (WSC), Seattle, USA, 2025.
Collaboration with KTH Royal Institute of Technology
WSC 2025
An Empirical Study on the Assessment of Demand Forecasting Reliability for Fabless Semiconductor Companies
I. Choi, S.-Y. Hwang, J. Ahn, J. Lee, S. Joo, K. Kim, H. Lee, Y. Song, and H.-J. Kim
Winter Simulation Conference (WSC), Seattle, USA, 2025.
Collaboration with Samsung Electronics
Paper
CASE 2025
Adaptive Self-Supervised Learning for Solving Flow Shop Scheduling Problems
I. Choi and H.-J. Kim
IEEE International Conference on Automation Science and Engineering (IEEE CASE), Los Angeles, USA, 2025.

Domestic

KIIE 2026
Graph Reinforcement Learning-based Integrated Scheduling for OLED TFT Array Manufacturing
S.-H. Cho, S.-H. Jung, I. Choi, B.-Y. Choi, B. Han, and H.-J. Kim
The Spring Conference of Korean Institute of Industrial Engineers (KIIE), Gyeongju, 2026.
Collaboration with Samsung Display
KIIE 2026
Natural Language-based Modification of Semiconductor Supply Management Spreadsheets using Retrieval-Augmented Generation
J. Park, I. Choi, S. Joo, Y. Kim, G. Oh, Y. Song, and H.-J. Kim
The Spring Conference of Korean Institute of Industrial Engineers (KIIE), Gyeongju, 2026.
Collaboration with Samsung Electronics
KIIE 2026
A Learning Framework for the Container Relocation Problem in Container Yards
W.-J. Shin, J.-K. Jung, S.-H. Cho, I. Choi, S. Tanaka, and H.-J. Kim
The Spring Conference of Korean Institute of Industrial Engineers (KIIE), Gyeongju, 2026.
KIIE 2026
Learning-Based UAV Path Planning for Clustered Reconnaissance Targets
W.-J. Shin, I. Choi, J.-Y. Shin, and H.-J. Kim
The Spring Conference of Korean Institute of Industrial Engineers (KIIE), Gyeongju, 2026.
KIIE 2025
A Self-Imitation Learning Framework for Neural Dispatching Rule Optimization
I. Choi and H.-J. Kim
The Spring Conference of Korean Institute of Industrial Engineers (KIIE), Jeju, 2025.
KIIE 2025
Multi-objective Scheduling for Photo Process Using Reinforcement Learning
S.-H. Cho, S.-H. Jung, I. Choi, B. Choi, B. Han, and H.-J. Kim
The Spring Conference of Korean Institute of Industrial Engineers (KIIE), Jeju, 2025.
Collaboration with Samsung Display
KIIE 2024
Deep Reinforcement Learning-based Encoder-Decoder Framework for The Clustered Traveling Salesman Problem
J. Park†, I. Choi†, S.-H. Cho, and H.-J. Kim
The Autumn Conference of Korean Institute of Industrial Engineers (KIIE), Seoul, 2024.
†: Co-first authors