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A hybrid approach for the dynamic flexible job shop scheduling problem considering machine failures.

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Title: A hybrid approach for the dynamic flexible job shop scheduling problem considering machine failures.
Authors: Peng, Chong1 (AUTHOR) pch@buaa.edu.cn, Zhang, Zhongwen1,2 (AUTHOR) zw@buaa.edu.cn, Liao, T. Warren3,4 (AUTHOR) ieliao@lsu.edu, Zhao, Hui1 (AUTHOR) 1183025150@qq.com, Cai, Yuzhen1 (AUTHOR) caiyuzhen@buaa.edu.cn
Source: Journal of Scheduling. Aug2025, Vol. 28 Issue 4, p407-424. 18p.
Subjects: Scheduling, Machine part failures, Artificial intelligence, Genetic algorithms, Industrial efficiency
Abstract: In practical production scheduling, dynamic disturbances such as machine failures frequently disrupt initial schedules. In this research, a new approach using a genetic algorithm prescheduling and machining path routing strategy is proposed to solve the dynamic flexible job shop scheduling problem. Firstly, the efficiency of the scheduling algorithm is improved by a genetic algorithm with an improved active decoding method and a rescheduling algorithm with a dual strategy of right shift and processing path rerouting. Then, a more reasonable solution is obtained by path rerouting in the framework of a prescheduling strategy using a binary tree-based identification system to determine the set of affected processes to reduce the restriction on alternative paths while increasing the search range. Finally, the proposed rescheduling algorithm is compared with two methods through experimental comparisons, which confirms that the algorithm can obtain a more robust and stable solution. [ABSTRACT FROM AUTHOR]
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Database: Engineering Source
Description
Abstract:In practical production scheduling, dynamic disturbances such as machine failures frequently disrupt initial schedules. In this research, a new approach using a genetic algorithm prescheduling and machining path routing strategy is proposed to solve the dynamic flexible job shop scheduling problem. Firstly, the efficiency of the scheduling algorithm is improved by a genetic algorithm with an improved active decoding method and a rescheduling algorithm with a dual strategy of right shift and processing path rerouting. Then, a more reasonable solution is obtained by path rerouting in the framework of a prescheduling strategy using a binary tree-based identification system to determine the set of affected processes to reduce the restriction on alternative paths while increasing the search range. Finally, the proposed rescheduling algorithm is compared with two methods through experimental comparisons, which confirms that the algorithm can obtain a more robust and stable solution. [ABSTRACT FROM AUTHOR]
ISSN:10946136
DOI:10.1007/s10951-025-00839-y