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Many-objective multi-task evolutionary method for flexible order production scheduling
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DOI：10.1016/j.eswa.2026.131817.png)
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Abstract
En 中文
• We proposed a many-objective multi-task model to address complex scheduling scenarios. • We propose an MTMOEA-LB to enhance knowledge transfer efficiency under task similarity. • Conduct scenario simulations and experiments using real-world data to highlight innovative.
Keywords:
Many-objective optimization
Multi-task learning
Evolutionary algorithm
Flexible order production
Scheduling
Journal
IF:
7.5
Papers:
2.9W
Citations:
10.2W