Sang-Hyun Cho — accepted AI-conference papers

2026

Preference-Guided Multi-Policy Optimization for Flexible Job Shop Scheduling

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

IJCAI 2026

Under the shift toward Industry 4.0, mass-customized manufacturing systems have introduced complex scheduling problems, such as the Flexible Job Shop Scheduling Problem (FJSSP). Recent Deep Reinforcement Learning (DRL)-based heuristics have shown promise, yet existing methods often suffer from two k

Cited by 0 Scholar ↗

2024

Dynamic Crane Scheduling with Reinforcement Learning for a Steel Coil Warehouse

Sang-Hyun Cho, Woo-Jin Shin, Jeongsun Ahn, Sanghyun Joo, Hyun-Jung Kim

ICRA 2024poster

This paper tackles the dynamic crane scheduling problem in a steel coil warehouse, involving tasks such as coil storage, retrieval, and shuffling. Tasks arrive dynamically with precedence relations, while multiple cranes share a track, necessitating collision avoidance. We aim to minimize the averag…

Cited by 3 Source ↗Scholar ↗