유전 알고리즘과 시뮬레이션을 통한 동적 스케줄링
A Genetic Algorithm and Discrete-Event Simulation Approach to the Dynamic Scheduling
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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 developedwork schedule applied to a real work area to verify that it could be executed in real work environment and remove the overlappingwork, 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.
Abstract
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 developedwork schedule applied to a real work area to verify that it could be executed in real work environment and remove the overlappingwork, 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.
참고문헌 (7)
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- Hong Zhou, "Minimizing weighted tardiness of job-shop scheduling using a hybrid genetic algorithm", European Journal of Operational Research, 194, pp.637~649 (2009)
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