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A variable window multi-interval rescheduling optimization algorithm for dynamic flexible job shop problem
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DOI：10.1016/j.asoc.2025.113157.png)
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Abstract
En 中文
The dynamic flexible workshop scheduling problem (DFJSP) requires the generation of new scheduling plans after being subjected to dynamic disturbances. Due to the reconfigurability of chromosomal gene, scheduling schemes have a large search space, which poses challenges for solving scheduling schemes. Therefore, a variable window multi-interval optimization (VWMI) rescheduling algorithm is proposed to solve the DFJSP. A nonlinear adaptive crossover probability and mutation probability function is proposed to address the issue of combinatorial optimization easily getting stuck in local optima. Based on the mapping relationship between individual space and objective space, a spatial joint selection method is proposed to select diverse individuals. Compared with other algorithms in dynamic workshop test cases, the rescheduling strategy achieved 7 optimal performance values in 15 test cases, with a maximum time efficiency improvement of 30.2%. In addition, the VWMI achieved 11 good performances in test cases, outperforming other optimization methods.
Keywords:
Dynamic flexible job shop scheduling
Multi-objective optimization
Window multi interval scheduling
Adaptive cross mutation probability
Neighborhood structure search
Journal
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6.6
Papers:
1.4W
Citations:
4.8W
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