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cs.LG2026
PLAN: Parallel Liquid-Inspired Approximation Network for Efficient Representation Learning in Flexible Job Shop Scheduling
Dhivya Dharshini Kannan, Wei Zhang, Jieyi Bi +5
Deep reinforcement learning (DRL) approaches for flexible job shop scheduling (FJSP) heavily rely on attention-centric architectures to achieve state-of-the-art performance. Howeve…
cs.LG2026
ReLA: Representation Learning and Aggregation for Job Scheduling with Reinforcement Learning
Zhengyi Kwan, Wei Zhang, Aik Beng Ng +2
Job scheduling is widely used in real-world manufacturing systems to assign ordered job operations to machines under various constraints. Existing solutions remain limited by long…