25 citations · 28 across the 11 of their papers we have counts for
4 papers · 1 filter
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…
Learning to Optimize Capacity Planning in Semiconductor Manufacturing
Philipp Andelfinger, Jieyi Bi, Qiuyu Zhu +7
In manufacturing, capacity planning is the process of allocating production resources in accordance with variable demand. The current industry practice in semiconductor manufacturi…
Generalizable Heuristic Generation Through LLMs with Meta-Optimization
Yiding Shi, Jianan Zhou, Wen Song +4
Heuristic design with large language models (LLMs) has emerged as a promising approach for tackling combinatorial optimization problems (COPs). However, existing approaches often r…
Learning Generalizable Models for Vehicle Routing Problems via Knowledge Distillation
Jieyi Bi, Yining Ma, Jiahai Wang +4
Recent neural methods for vehicle routing problems always train and test the deep models on the same instance distribution (i.e., uniform). To tackle the consequent cross-distribut…