9 citations · 34 across the 18 of their papers we have counts for
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cs.LG2023★ 9 cited
Learning to Search Feasible and Infeasible Regions of Routing Problems with Flexible Neural k-Opt
Yining Ma, Zhiguang Cao, Yeow Meng Chee
In this paper, we present Neural k-Opt (NeuOpt), a novel learning-to-search (L2S) solver for routing problems. It learns to perform flexible k-opt exchanges based on a tailored act…
cs.LG2023★ 5 cited
MetaBox: A Benchmark Platform for Meta-Black-Box Optimization with Reinforcement Learning
Zeyuan Ma, Hongshu Guo, Jiacheng Chen +5
Recently, Meta-Black-Box Optimization with Reinforcement Learning (MetaBBO-RL) has showcased the power of leveraging RL at the meta-level to mitigate manual fine-tuning of low-leve…
cs.LG2023★ 3 cited
Neural Multi-Objective Combinatorial Optimization with Diversity Enhancement
Jinbiao Chen, Zizhen Zhang, Zhiguang Cao +4
Most of existing neural methods for multi-objective combinatorial optimization (MOCO) problems solely rely on decomposition, which often leads to repetitive solutions for the respe…