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BOLT: Multi-Bottleneck Bound-Guided Learning for Flexible Job-Shop Scheduling with Time Lags and Resource-Coupled Transport
Not provided in the abstract
schedulingoptimizationtransportationmachine learning
2610.22433
Builder Relevance
1h ago80%
Abstract
BOLT improves flexible job-shop scheduling by effectively managing transport coupling and optimizing makespan.
Reality Card
Core Claim
BOLT outperforms existing scheduling policies, achieving a mean makespan 13.0% below the best dispatching-rule pair in a three-vehicle 80-module batch.
Method / Result
BOLT decides in 2.3-5.9 ms per event and replans disruptions in seconds.
Limitations
The paper does not provide detailed author information or specific experimental setups, which may hinder reproducibility.
Paper to code
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