Dynamic flexible job shop scheduling (DFJSP) with job insertions is a representative challenge in modern manufacturing systems, where dispatching decisions must continuously adapt to evolving shop-floor states. In such event-driven settings, effective reinforcement learning hinges on state representations that can simu...
Dynamic industrial processes operate in time-varying environments with conflicting objectives, making realtime optimization difficult. Traditional scalarization methods use fixed objective weights and fail when conditions change. Evolutionary multi-objective algorithms can approximate the Pareto front but are too compu...
This survey focuses on how cloud-side large models and edge-side small models share, update, and coordinate knowledge and identifies open challenges for trustworthy, sustainable, and self-evolving cloud–edge collaborative intelligence.
Yaxi Yang, Jing-Ye Bi, Haitao Yuan et al.· Journal of Artificial Intell...· 0 citations
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