most citedResidual Scheduling: A New Reinforcement Learning Approach to Solving Job Shop Scheduling Problem

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cs.AI2026

A Robust and Efficient Multi-Agent Reinforcement Learning Framework for Traffic Signal Control

Sheng-You Huang, Hsiao-Chuan Chang, Yen-Chi Chen +6

Reinforcement Learning (RL) in Traffic Signal Control (TSC) faces significant hurdles in real-world deployment due to limited generalization to dynamic traffic flow variations. Exi…

cs.AI2023★ 1 cited

Residual Scheduling: A New Reinforcement Learning Approach to Solving Job Shop Scheduling Problem

Kuo-Hao Ho, Ruei-Yu Jheng, Ji-Han Wu +4

Job-shop scheduling problem (JSP) is a mathematical optimization problem widely used in industries like manufacturing, and flexible JSP (FJSP) is also a common variant. Since they…