A Reinforcement Learning Approach to Robust Scheduling of Semiconductor Manufacturing Facilities. - In-Beom Park; Jaeseok Huh; Joongkyun Kim; Jonghun Park (IEEE Trans Autom. Sci. Eng., 2020)

Deep Reinforcement Learning for Minimizing Tardiness in Parallel Machine Scheduling With Sequence Dependent Family Setups. - Bohyung Paeng; In-Beom Park; Jonghun Park (IEEE Access, 2021)

A Generation and Repair Approach to Scheduling Semiconductor Packaging Facilities Using Case-Based Reasoning. - In-Beom Park; Jaeseok Huh; Jonghun Park (IEEE Access, 2023)

Scalable Scheduling of Semiconductor Packaging Facilities Using Deep Reinforcement Learning. - In-Beom Park; Jonghun Park (IEEE Trans. Cybern., 2023)

An incremental learning approach to dynamic parallel machine scheduling with sequence-dependent setups and machine eligibility restrictions. - Donghun Lee; In-Beom Park; Kwanho Kim (Appl. Soft Comput., 2024)

A self-imitation learning approach for scheduling evaporation and encapsulation stages of OLED display manufacturing systems. - Donghun Lee; In-Beom Park; Kwanho Kim (Robotics Comput. Integr. Manuf., 2025)