This study develops a dynamic scheduling model for parallel machine scheduling problem based on genetic algorithm (GA). GA combined with discrete event simulation to minimize the makespan and verifies the effectiveness of the developed model. This research consists of two stages. In the first stage, work sequence will be generated using GA, and the second stage developed work schedule applied to a real work area to verify that it could be executed in real work environment and remove the overlapping work, which causes bottleneck and long lead time. If not, go back to the first stage and develop another schedule until satisfied. Small size problem was experimented and suggested a reasonable schedule within limited resources. As a result of this research, work efficiency is increased, cycle time is decreased, and due date is satisfied within existed resources.

• Sanghan Yoon(Daegyeong Institute for Regional Program Evaluation) | 윤상한
• Jonghwan Lee(School of Industrial Engineering, Kumoh National Institute of Technology) | 이종환 Corresponding Author
• Gwan-Young Jung(School of Industrial Engineering, Kumoh National Institute of Technology) | 정관영
• Hyunsoo Lee(School of Industrial Engineering, Kumoh National Institute of Technology) | 이현수
• Doyeong Wie(School of Industrial Engineering, Kumoh National Institute of Technology) | 위도영
• Jiyong Jeong(School of Industrial Engineering, Kumoh National Institute of Technology) | 정지용
• Yeongbok Seo(School of Industrial Engineering, Kumoh National Institute of Tech) | 서영복