Sep 2026· International Journal of Machine Learning and Cybernetics· Vol 17· 0 citations· 36 references
Scheduling and Optimization Algorithms
TL;DR
The State Extraction Graph (SEG) is proposed, which provides a significantly more concise structural representation than Petri nets for modeling multi-wafer fabrication processes and a Graph Deep Reinforcement Learning (G-DRL) method for scheduling cluster tools.
A novel end-to-end, size-agnostic graph reinforcement learning framework for 1D-BPP that outperforms a state-of-the-art learned solver that relies on column generation and integer programming, while using no solver at all.
A deep recurrent Q-network (DRQN)-based framework for post-placement circuit optimization that jointly leverages all three operations to enable integrated optimization of timing and power and design a reward function that applies symmetric logarithmic compression to each metric at a fixed scale, allowing controllable t...
Kijung Kong, Heechun Park· International Symposium on L...· 0 citations
This work proposes HiGFRL, a Hierarchical Graph Fusion-Driven Reinforcement Learning framework, which designs a fusion-driven dual-network architecture to optimize RL decision-making and incorporates a topology-prior-guided hybrid reward mechanism that distills static topological priors into the learning process to acc...
An extended FJSP with multiple BPMs is formed and an end-to-end two-layer multi-agent deep reinforcement learning framework is proposed, supporting the framework as an effective scheduling approach for deterministic FJSP with BPMs and indicating cross-scale generalization across evaluated instances.
This work proposes PLAN (Parallel Liquid-inspired Approximation Network), a lightweight representation learning framework that reformulates continuous liquid-state dynamics into a discretized and parallelizable formulation and acts as a versatile, plug-and-play backbone that generalizes to complex FJSP variants.
D. D. Kannan, Wei Zhang, Jieyi Bi et al.· 0 citations
: The Permutation Flow Shop Scheduling Problem (PFSP) is one of the most classic combinatorial optimization problems in manufacturing systems, with wide applications in semiconductor fabrication, textile processing, and steelmaking. The Permutation Flow Shop Scheduling Problem with Sequence-Dependent Setup Times (PFSP-...
Bo-On-Chua Wei, Hong-Feng Wang· Computers, Materials & C...· 0 citations
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