A unified learning framework for the block relocation problem: A new performance baselineWoo-Jin Shin*, Ji-Kwang Jung*, Sang-Hyun Cho, Inguk Choi, Shunji Tanaka, Hyun-Jung Kim†European Journal of Operational Research (EJOR), online published, 2026 (SCIE, JCR 9.6%)Link
Monte Carlo tree search for the multi-crane scheduling problem with temporal constraintsWoo-Jin Shin*, Seungkyu Yoon*, Hyun-Jung Kim†Flexible Services and Manufacturing Journal (FSMJ), online published, 2026 (SCIE, JCR 29.8%)Link
Learning to retrieve containers: A scale-diverse deep reinforcement learning approach for the container retrieval problemWoo-Jin Shin, Inguk Choi, Sang-Hyun Cho, Hyun-Jung Kim†Transportation Research Part C: Emerging Technologies (TR-C), vol. 183, art. 105496, 2026 (SCIE, JCR 13.1%)Link
Advances in multi-crane scheduling: Extended non-interference modeling and temporal-constraint-based valid inequalitiesWoo-Jin Shin, Hyun-Jung Kim†European Journal of Operational Research (EJOR), vol. 331, no. 1, pp. 35-47, 2026 (SCIE, JCR 9.6%)Link
Scheduling of steelmaking-continuous casting process by integrating deep neural networks with mixed integer programmingWoo-Jin Shin, Sang-Wook Lee, J. Lee, M. Song, Hyun-Jung Kim†International Journal of Production Research (IJPR), vol. 63, no. 11, pp. 4180-4201, 2025 (SCIE, JCR 7.8%)Link
ML · 로보틱스 학회 논문
Towards a unified model for flexible job shop scheduling problemsInguk Choi, Woo-Jin Shin, Sang-Hyun Cho, Hyun-Jung Kim†Neural Information Processing Systems (NeurIPS), 2026
Towards generalizable multi-policy optimization with self-evolution for job schedulingInguk Choi, Woo-Jin Shin, Sang-Hyun Cho, Hyun-Jung Kim†Neural Information Processing Systems (NeurIPS), pp. 27837-27884, 2025Link
Dynamic crane scheduling with reinforcement learning for a steel coil warehouseSang-Hyun Cho*, Woo-Jin Shin*, Jeongsun Ahn, Sanghyun Joo, Hyun-Jung Kim†IEEE International Conference on Robotics and Automation (ICRA), pp. 16545-16552, 2024Link
진행 중인 논문
AI transformation in manufacturing: Across materials, processes, equipment, and factoriesIn collaboration with the Department of Mechanical Engineering, KAIST심사 중
Deep reinforcement learning for adaptive scheduling parameter control in queue-time-constrained wafer fab operationsDong-Yoon Oh, Yuchul Lim, Woo-Jin Shin, Hyun-Jung Kim심사 중
A machine learning-accelerated logic-based Benders decomposition for the stack loading problemKaren Seojin Kim, Woo-Jin Shin, Hyun-Jung Kim심사 중
Deep reinforcement learning for dynamic machine scheduling: Insights into update interval and reward designJiansong Wan, Woo-Jin Shin, Sungyeon Lim, Hyun-Jung Kim, Hayong Shin심사 중
Learning-based UAV path planning for clustered reconnaissance targetsWoo-Jin Shin, Inguk Choi, Hyun-Jung Kim준비 중
Bi-objective parallel machine scheduling for the upstream process (USP) in biopharmaceutical productionWoo-Jin Shin, Seonyoung Hwang, Hyun-Jung Kim준비 중
Branch and bound algorithm for the multi-crane scheduling problem with temporal constraintsWoo-Jin Shin, Hyun-Jung Kim준비 중
Parallel machine scheduling with additional resources: A real-world application in tire manufacturingHong-Yeon Kim, Woo-Jin Shin, Sanghyun Joo, Hyun-Jung Kim준비 중
국제학회 발표
Learning-based scheduling for stochastic job shop scheduling with mobile robotsW.-J. Shin, D. Oh, I. Choi, M. Wiktorsson, E. Flores-García, Y. Jeong, H.-J. Kim†Winter Simulation Conference (WSC), Seattle, USA, 2025
Mathematical models and heuristics for the multi-crane scheduling problem with temporal constraintsWoo-Jin Shin, Hyun-Jung Kim†11th IFAC Conference on Manufacturing Modelling, Management and Control (IFAC MIM), vol. 59, no. 10, pp. 2515-2520, Trondheim, Norway, 2025Link
Deep reinforcement learning for the container retrieval problemWoo-Jin Shin, Ji-Kwang Jung, Sang-Hyun Cho, Hyun-Jung Kim†IEEE 21st International Conference on Automation Science and Engineering (CASE), Los Angeles, USA, 2025Link
Resource-constrained parallel machine scheduling for tire manufacturingHong-Yeon Kim, Woo-Jin Shin, Sanghyun Joo, Hyun-Jung Kim†IEEE 21st International Conference on Automation Science and Engineering (CASE), Los Angeles, USA, 2025Link
Graph-based deep reinforcement learning for crane scheduling with temporal constraintsW.-J. Shin, H.-J. Kim†IEEE International Conference on Automation Science and Engineering (CASE), Bari, Italy, 2024
Block relocation problem with deep reinforcement learningJ.-K. Jung, S.-H. Cho, W.-J. Shin, H.-J. Kim†IEEE International Conference on Automation Science and Engineering (CASE), Bari, Italy, 2024
Dynamic crane scheduling with reinforcement learningW.-J. Shin, S.-H. Cho, J. Ahn, S. Joo, H.-J. Kim†The 7th International Workshop on Production and Logistics (IWPL), Yokohama, Japan, 2024
An efficient simulation-based optimization algorithm for a crane scheduling problem in a steelmaking shopW.-J. Shin, H.-J. Kim†Winter Simulation Conference (WSC), San Antonio, USA, 2023
An exact algorithm for the crane scheduling problem in a steelmaking shopW.-J. Shin, H.-J. Kim†IEEE International Conference on Automation Science and Engineering (CASE), Auckland, New Zealand, 2023
Single machine scheduling with job quality levels for battery manufacturingS.-W. Lee, W.-J. Shin, H.-J. Kim†INFORMS Annual Meeting, Online, 2021
Integrated scheduling of machines and cranes for steelmaking-continuous casting productionW.-J. Shin, S.-W. Lee, S.-S. Park, H.-J. Kim†INFORMS Annual Meeting, Online, 2021
국내학회 발표
Learning-based UAV path planning for clustered reconnaissance targetsW.-J. Shin, I. Choi, J.-Y. Shin, H.-J. Kim†The Spring Conference of Korean Institute of Industrial Engineers (KIIE), Gyeongju, 2026
A learning framework for the container relocation problem in container yardsW.-J. Shin, J.-K. Jung, S.-H. Cho, I. Choi, S. Tanaka, H.-J. Kim†The Spring Conference of Korean Institute of Industrial Engineers (KIIE), Gyeongju, 2026
Dynamic control of scheduling parameters for semiconductor production lines under uncertaintyD.-Y. Oh, Y. Lim, W.-J. Shin, H.-J. Kim†The Spring Conference of Korean Institute of Industrial Engineers (KIIE), Gyeongju, 2026
Solving the container retrieval problem using a deep reinforcement learning approachW.-J. Shin, H.-J. Kim†The Spring Conference of Korean Institute of Industrial Engineers (KIIE), Jeju, 2025
Novel non-interference strategy and mixed integer programming models for the multi-crane scheduling problemW.-J. Shin, H.-J. Kim†The Autumn Conference of Korean Institute of Industrial Engineers (KIIE), Seoul, 2024
Self-supervised imitation learning for the blocks relocation problemS.-H. Cho, W.-J. Shin, J.-K. Jung, H.-J. Kim†The Autumn Conference of Korean Institute of Industrial Engineers (KIIE), Seoul, 2024
Crane scheduling with graph-based deep reinforcement learningW.-J. Shin, H.-J. Kim†The Spring Conference of Korean Institute of Industrial Engineers (KIIE), Yeosu, 2024
Resource-constrained parallel machine schedulingH.-Y. Kim, W.-J. Shin, S.-H. Joo, C.-W. Kim, T.-J. Park, M.-J. Kim, H.-J. Kim†The Spring Conference of Korean Institute of Industrial Engineers (KIIE), Yeosu, 2024
Solving the dynamic crane scheduling problem in a steel coil warehouse with reinforcement learningW.-J. Shin, S.-H. Cho, J. Ahn, S. Joo, H.-J. Kim†The Autumn Conference of Korean Institute of Industrial Engineers (KIIE), Ulsan, 2023
Scheduling application cases: Focused on insulation material productionH.-J. Kim†, W.-J. Shin, S.-W. Lee, C.-Y. Kim, I. Song, S. Moon, S. Lee, D. SeoThe Spring Conference of Korean Institute of Industrial Engineers (KIIE), Jeju, 2023
Crane scheduling problem in a steelmaking shopW.-J. Shin, H.-J. Kim†The Spring Conference of Korean Institute of Industrial Engineers (KIIE), Jeju, 2023
Machine learning and mixed integer programming for the machine assignment in steelmaking-processW.-J. Shin, S.-W. Lee, M. Song, Y. Kim, J.-H. Lee, H.-J. Kim†The Autumn Conference of Korean Institute of Industrial Engineers (KIIE), Incheon, 2022
Machine assignment for steelmaking-continuous casting manufacturing with machine learningS.-W. Lee, W.-J. Shin, M. Song, Y. Kim, J.-H. Lee, H.-J. Kim†The Spring Conference of Korean Institute of Industrial Engineers (KIIE), Jeju, 2022
