Open AccessA rescheduling approach based on genetic algorithm for flexible scheduling problem subject to machine breakdown
Author(s) -
Lei Nie,
Xiaogang Wang,
Kai Liu,
Yuewei Bai
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1453/1/012018
Subject(s) - computer science , robustness (evolution) , scheduling (production processes) , benchmark (surveying) , mathematical optimization , job shop scheduling , genetic algorithm , algorithm , routing (electronic design automation) , mathematics , machine learning , embedded system , biochemistry , chemistry , geodesy , gene , geography
In this paper, a rescheduling approach based on genetic algorithm (GA) for solving the flexible scheduling problem subject to machine breakdown is proposed. In the proposed approach, event-driven rolling horizon rescheduling policy is employed to trigger the rescheduling procedure. Computational experiments are conducted on several benchmark data to prove the performance of the proposed approach. The results show that the proposed approach combines the rescheduling strategies of right-shift rescheduling and routing changing rescheduling to optimize the robustness and stability of rescheduling solution simultaneously.