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cs.LG2024
Offline reinforcement learning for job-shop scheduling problems
Imanol Echeverria, Maialen Murua, Roberto Santana
Recent advances in deep learning have shown significant potential for solving combinatorial optimization problems in real-time. Unlike traditional methods, deep learning can genera…
cs.AI2024★ 1 cited
Leveraging Constraint Programming in a Deep Learning Approach for Dynamically Solving the Flexible Job-Shop Scheduling Problem
Imanol Echeverria, Maialen Murua, Roberto Santana
Recent advancements in the flexible job-shop scheduling problem (FJSSP) are primarily based on deep reinforcement learning (DRL) due to its ability to generate high-quality, real-t…