IngukChoi Homepage - Publications

🚀 Under Review/Accepted

Woo-Jin Shin, Ji-Kang Jung, Sang-Hyun Cho, Inguk Choi, Shunji Tanaka, and Hyun-Jung Kim, "A Unified Learning Framework for the Block Relocation Problem: A New Performance Baseline"
- Under review at European Journal of Operational Research (EJOR)
Inguk Choi, Woo-Jin Shin, Sang-Hyun Cho, and Hyun-Jung Kim, "Preference-Guided Multi-Policy Optimization for Solving Flexible Job Shop Scheduling"
- Under review at International Joint Conference on Artificial Intelligence (IJCAI 2026)

📖 Publications

Woo-Jin Shin, Inguk Choi, Sang-Hyun Cho, and Hyun-Jung Kim, "Learning to Retrieve Containers: A Scale-Diverse Deep Reinforcement Learning Approach for the Container Retrieval Problem", Transportation Research Part C: Emerging Technologies (TR-C), vol.183, 2026. (SCIE, Q1) [Paper]
(†: Co-first) Jimin Park†, Inguk Choi†, and Hyun-Jung Kim, "A Multi-View Attention-Based Encoder-Decoder Framework for Clustered Traveling Salesman Problem", IEEE Robotics and Automation Letters (IEEE RA-L), vol.11, no.1, pp.137-144, 2026. (SCIE, Q1) [Paper]
Inguk Choi, Seon-Young Hwang, Jeogsun Ahn, Jehun Lee, Sanghyun Joo, Kiung Kim, Haechan Lee, Yoong Song, and Hyun-Jung Kim (with Samsung Electronics) "An Empirical Study on the Assessment of Demand Forecasting Reliability for Fabless Semiconductor Companies", Winter Simulation Conference (WSC), Seattle, USA, 2025. [Paper]
Inguk Choi, Woo-Jin Shin, Sang-Hyun Cho, and Hyun-Jung Kim, "Towards Generalizable Multi-Policy Optimization with Self-Evolution for Job Scheduling", The Thirty-Ninth Annual Conference on Neural Information Processing Systems (NeurIPS), San Diego, USA, 2025. (Top AI Conference) [Paper]

🗣 Conference Presentation Only

W.-J. Shin, D. Oh, I. Choi, M. Wiktorsson, E. Flores-García, Y. Jeong, and H.-J. Kim (with KTH Royal Institute of Technology), "Learning-based Scheduling for Stochastic Job Shop Scheduling with Mobile Robots", Winter Simulation Conference (WSC), Seattle, USA, 2025.
I. Choi and H.-J. Kim, "Adaptive Self-Supervised Learning for Solving Flow Shop Scheduling Problems", IEEE International Conference on Automation Science and Engineering (IEEE CASE), Los Angeles, USA, 2025.

I. Choi, H.-J. Kim, "A Self-Imitation Learning Framework for Neural Dispatching Rule Optimization ", The Spring Conference of Korea Institute of Industrial Engineers, Jeju, South Korea, 2025.
S.-H. Cho, S.-H. Jung, I. Choi, B. Choi, B. Han, and H.-J. Kim, "Multi-objective Scheduling for Photo Process Using Reinforcement Learning", The Spring Conference of Korean Institute of Industrial Engineers, Jeju, South Korea, 2025.
(†: Co-first) J. Park†, I. Choi†, S.-H. Cho and H.-J. Kim, "Deep Reinforcement Learning-based Encoder-Decoder Framework for The Clustered Traveling Salesman Problem", The Autumn Conference of Korea Institute of Industrial Engineers, Seoul, South Korea, 2024.