Preference learning based deep reinforcement learning for flexible job shop scheduling problem
Abstract The flexible job shop scheduling problem (FJSP) holds significant importance in both theoretical research and practical applications. Given the complexity and diversity of FJSP, improving the generalization and quality of scheduling methods has become a hot topic of interest in both industr...
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Main Authors: | , , , , |
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Format: | Article |
Language: | English |
Published: |
Springer
2025-01-01
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Series: | Complex & Intelligent Systems |
Subjects: | |
Online Access: | https://doi.org/10.1007/s40747-024-01772-x |
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