Research Interests

• Production & Logistics Scheduling

  • AI-enabled scheduling

  • Operations research methods

  • Neural combinatorial optimization

Professional Experience

• Postdoctoral Researcher, Korea Advanced Institute of Science and Technology (KAIST)

  • Mar 2026 – Present

• Research Assistant, The Institute of Intelligent Logistics Big Data, Pusan National University

  • Sep 2020 – Jan 2021

  • Supervisor: Prof. Soondo Hong

  • Project: FAB simulation and learning-based machine selection algorithm development

Publications

Journal Articles

1. "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, art. 105496, 2026. (SCIE, Q1)

2. "Advances in multi-crane scheduling: Extended non-interference modeling and temporal-constraint-based valid inequalities"

   • Woo-Jin Shin and Hyun-Jung Kim

   • European Journal of Operational Research (EJOR), vol. 331, no. 1, pp. 35 - 47, 2026. (SCIE, Q1)

3. "Scheduling of steelmaking-continuous casting process by integrating deep neural networks with mixed integer programming"

   • Woo-Jin Shin, Sang-Wook Lee, Jun-Ho Lee, Min-Ho Song, and Hyun-Jung Kim

   • International Journal of Production Research (IJPR), vol. 63, no. 11, pp. 4180 - 4201, 2025. (SCIE, Q1)

Top-Tier & Major Conference Papers

1. "Towards generalizable multi-policy optimization with self-evolution for job scheduling"

   • Inguk Choi, Woo-Jin Shin, Sang-Hyun Cho, and Hyun-Jung Kim

   • Neural Information Processing Systems (NeurIPS), 2025.

2. "Dynamic crane scheduling with reinforcement learning for a steel coil warehouse"

3. • (* Co-first) Sang-Hyun Cho*, Woo-Jin Shin*, Jeongsun Ahn, Sanghyun Joo, and Hyun-Jung Kim

   • IEEE International Conference on Robotics and Automation (ICRA), 2024.

Other Peer-Reviewed Conference Papers

1. "Mathematical models and heuristics for the multi-crane scheduling problem with temporal constraints"

   • Woo-Jin Shin and Hyun-Jung Kim

   • 11th IFAC Conference on Manufacturing Modelling, Management and Control MIM. IFAC-PapersOnLine, vol 59, no. 10, pp. 2515 - 2520, 2025.

2. "Deep reinforcement learning for the container retrieval problem"

   • Woo-Jin Shin, Ji-Kwang Jung, Sang-Hyun Cho, and Hyun-Jung Kim

   • IEEE 21st International Conference on Automation Science and Engineering (CASE). IEEE, 2025.

3. "Resource-constrained parallel machine scheduling for tire manufacturing"

3. • Hong-Yeon Kim, Woo-Jin Shin, Sanghyun Joo, and Hyun-Jung Kim

   • IEEE 21st International Conference on Automation Science and Engineering (CASE). IEEE, 2025.

Working Papers

Under Review

1. "Monte Carlo Tree Search for the multi-crane scheduling problem with temporal constraints"

   • Woo-Jin Shin, Seung-Kyu Yoon, and Hyun-Jung Kim

   • Under review at FSMJ

2. "A unified learning framework for the block relocation problem: A new performance baseline"

   • Woo-Jin Shin, Ji-Kwang Jung, Sang-Hyun Cho, Inguk Choi, Shunji Tanaka, and Hyun-Jung Kim

   • Under review at EJOR

3. "Preference-guided multi-policy optimization for flexible job shop scheduling"

   • Inguk Choi, Woo-Jin Shin, Sang-Hyun Cho, and Hyun-Jung Kim

   • Under review at IJCAI

4. "Deep reinforcement learning for dynamic machine scheduling: Insights into update interval and reward design"

   • Jiansong Wan, Woo-Jin Shin, Sungyeon Lim, Hyun-Jung Kim, and Hayong Shin

   • Major revision at EJOR

In Preparation

1. "Bi-objective parallel machine scheduling for the upstream process (USP) in biopharmaceutical production"

   • Woo-Jin Shin, Seonyoung Hwang, and Hyun-Jung Kim

2. "Branch and bound algorithm for the multi-crane scheduling problem with temporal constraints"

   • Woo-Jin Shin and Hyun-Jung Kim

3. "Parallel machine scheduling with additional resources: A real-world application in tire manufacturing"

4. • Hong-Yeon Kim, Woo-Jin Shin, Sanghyun Joo, and Hyun-Jung Kim

Conference Presentation Only

1. "Learning-based scheduling for stochastic job shop scheduling with mobile robots"

   • W.-J. Shin, D. Oh, I. Choi, M. Wiktorsson, E. Flores-García, Y. Jeong, and H.-J. Kim

   • Winter Simulation Conference (WSC), Seattle, USA, 2025

2. "Solving the container retrieval problem using a deep reinforcement learning approach"

   • W.-J. Shin and H.-J. Kim

   • The Spring Conference of Korean Institute of Industrial Engineers (KIIE), Jeju, 2025

3. "A novel non-interference strategy and mixed integer programming models for the multi-crane scheduling problem"

   • W.-J. Shin and H.-J. Kim

   • The Autumn Conference of Korean Institute of Industrial Engineers (KIIE), Seoul, 2024

4. "Self-supervised imitation learning for the blocks relocation problem"

   • S.-H. Cho, W.-J. Shin, J.-K. Jung, and H.-J. Kim

   • The Autumn Conference of Korean Institute of Industrial Engineers (KIIE), Seoul, 2024

5. "Graph-based deep reinforcement learning for crane scheduling with temporal constraints"

   • W.-J. Shin and H.-J. Kim

   • IEEE International Conference on Automation Science and Engineering (CASE), Bari, Italy, 2024

6. "Block relocation problem with deep reinforcement learning"

   • J.-K. Jung, S.-H. Cho, W.-J. Shin, and H.-J. Kim

   • IEEE International Conference on Automation Science and Engineering (CASE), Bari, Italy, 2024

7. "Crane scheduling with graph-based deep reinforcement learning"

   • W.-J. Shin and H.-J. Kim

   • The Spring Conference of Korean Institute of Industrial Engineers (KIIE), Yeosu, 2024

8. "Resource-constrained parallel machine scheduling"

   • H.-Y. Kim, W.-J. Shin, S.-H. Joo, C.-W. Kim, T.-J. Park, M.-J. Kim, and H.-J. Kim

   • The Spring Conference of Korean Institute of Industrial Engineers (KIIE), Yeosu, 2024

9. "Dynamic crane scheduling with reinforcement learning"

   • W.-J. Shin, S.-H. Cho, J. Ahn, S. Joo, and H.-J. Kim

   • The 7th International Workshop on Production and Logistics (IWPL), Yokohama, Japan, 2024

10. "An efficient simulation-based optimization algorithm for a crane scheduling problem in a steelmaking shop"

    • W.-J. Shin and H.-J. Kim

    • Winter Simulation Conference (WSC), San Antonio, USA, 2023

11. "Solving the dynamic crane scheduling problem in a steel coil warehouse with reinforcement learning"

    • W.-J. Shin, S.-H. Cho, J. Ahn, S. Joo, and H.-J. Kim

    • The Autumn Conference of Korean Institute of Industrial Engineers (KIIE), Ulsan, 2023

12. "An exact algorithm for the crane scheduling problem in a steelmaking shop"

    • W.-J. Shin and H.-J. Kim

    • IEEE International Conference on Automation Science and Engineering (CASE), Auckland, New Zealand, 2023

13. "Scheduling application cases: Focused on insulation material production"

    • H.-J. Kim, W.-J. Shin, S.-W. Lee, C.-Y. Kim, I. Song, S. Moon, S. Lee, and D. Seo

    • The Spring Conference of Korean Institute of Industrial Engineers (KIIE), Jeju, 2023

14. "Crane scheduling problem in a steelmaking shop"

    • W.-J. Shin and H.-J. Kim

    • The Spring Conference of Korean Institute of Industrial Engineers (KIIE), Jeju, 2023

15. "Machine learning and mixed integer programming for the machine assignment in steelmaking-process"

    • W.-J. Shin, S.-W. Lee, M. Song, Y. Kim, J.-H. Lee, and H.-J. Kim

    • The Autumn Conference of Korean Institute of Industrial Engineers (KIIE), Incheon, 2022

16. "Machine assignment for steelmaking-continuous casting manufacturing with machine learning"

    • S.-W. Lee, W.-J. Shin, M. Song, Y. Kim, J.-H. Lee, and H.-J. Kim

    • The Spring Conference of Korean Institute of Industrial Engineers (KIIE), Jeju, 2022

17. "Single machine scheduling with job quality levels for battery manufacturing"

    • S.-W. Lee, W.-J. Shin, and H.-J. Kim

    • INFORMS Annual Meeting, Online, 2021

18. "Integrated scheduling of machines and cranes for steelmaking-continuous casting production"

    • W.-J. Shin, S.-W. Lee, S.-S. Park, and H.-J. Kim

    • INFORMS Annual Meeting, Online, 2021

Industrial Research Projects

1. 반도체 Fab 생산 예측 시뮬레이션 활용 강화학습 연구 (Mar 2026 - Present)

   • with Samsung Electronics

   • Project: RL-based adaptive parameter optimization for lot dispatching in semiconductor Fabs

2. 시운전 프로젝트 스케줄링 (Nov 2024 – Oct 2025)

   • with Samsung E&A

   • Project: Large-scale project scheduling for plant construction and commissioning

3. 설계 DB 내 유사회로 탐색을 위한 Circuit Recognition (Mar 2024 – Oct 2024)

   • with SK Hynix

   • Project: Circuit recognition for pattern detection

4. 디지털트윈 기반 반제품 생산 스케줄링 (Nov 2023 – Oct 2024)

   • with Hankook Tire & Technology

   • Project: Scheduling of tire manufacturing lines

5. 강화학습 기반 크레인 스케줄링 (Jul 2023 – Dec 2023)

   • with AI Platform Center for Manufacturing at KAIST

   • Project: RL-based multi-crane scheduling in coil warehousing systems

   • Research outcome: Published a research paper titled “Dynamic crane scheduling with reinforcement learning for a steel coil warehouse” in IEEE International Conference on Robotics and Automation (ICRA), Yokohama, Japan, 2024.

6. 최적화 기반의 제강 크레인 관제 알고리즘 개발 (Oct 2022 – Sep 2023)

   • with POSCO

   • Project: Multi-crane and ladle scheduling in steelmaking processes

7. 최적 혼류 생산계획 수립 모델 개발 (May 2022 – Dec 2022)

   • with LG Electronics

   • Project: Mixed-product production line scheduling for thermal insulation manufacturing

8. 반도체 자동 반송장비 OHT 시스템 트랙 이물질 감지 알고리즘 개발 (Jul 2021 – Dec 2021)

   • with AI Platform Center for Manufacturing at KAIST

   • Project: Semiconductor OHT system simulation and abnormal event detection

9. 제강 Crane 관제 알고리즘 개발 (Jun 2021 – May 2022)

   • with POSCO

   • Project: AI–optimization integrated scheduling for steelmaking production systems

   • Research outcome: Published a research paper titled “Scheduling of steelmaking-continuous casting process by integrating deep neural networks with mixed integer programming” in International Journal of Production Research (IJPR), vol. 63, no. 11, pp.4180-4201, 2025.

Awards

1. Best Ph.D. Dissertation Award

   • College of Engineering, KAIST, 2026

2. Grand Prize, Next-Generation Engineering Researcher Award

   • Institute for the Promotion of Engineering and Science of Korea (IPESK), 2025

3. Grand Prize, Poster Competition for Industrial/Social Problem Solving

   • Department of Industrial and Systems Engineering, KAIST, 2024

4. Grand Prize, Advanced Manufacturing and Smartification Challenge

   • AI Platform Center for Manufacturing at KAIST, 2024

5. 1st Place Award, Simulation Challenge

   • Winter Simulation Conference (WSC), 2023

6. Excellent Prize, Master’s Thesis Competition

   • Korean Institute of Industrial Engineers (KIIE), 2023

Contact

• wjshin@kaist.ac.kr

• +82 10-5611-5790

• https://msslab.kaist.ac.kr/