3 citations · 5 across the 4 of their papers we have counts for
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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…
cs.AI2023★ 3 cited
Solving the flexible job-shop scheduling problem through an enhanced deep reinforcement learning approach
Imanol Echeverria, Maialen Murua, Roberto Santana
In scheduling problems common in the industry and various real-world scenarios, responding in real-time to disruptive events is essential. Recent methods propose the use of deep re…