1 citations · 1 across the 5 of their papers we have counts for
7 papers
Learning Memory-Enhanced Improvement Heuristics for Flexible Job Shop Scheduling
Jiaqi Wang, Zhiguang Cao, Peng Zhao +4
The rise of smart manufacturing under Industry 4.0 introduces mass customization and dynamic production, demanding more advanced and flexible scheduling techniques. The flexible jo…
iPEAR: Iterative Pyramid Estimation with Attention and Residuals for Deformable Medical Image Registration
Heming Wu, Di Wang, Tai Ma +6
Existing pyramid registration networks may accumulate anatomical misalignments and lack an effective mechanism to dynamically determine the number of optimization iterations under…
Efficient Neural Combinatorial Optimization Solver for the Min-max Heterogeneous Capacitated Vehicle Routing Problem
Xuan Wu, Di Wang, Chunguo Wu +5
Numerous Neural Combinatorial Optimization (NCO) solvers have been proposed to address Vehicle Routing Problems (VRPs). However, most of these solvers focus exclusively on single-v…
Towards Efficient Few-shot Graph Neural Architecture Search via Partitioning Gradient Contribution
Wenhao Song, Xuan Wu, Bo Yang +6
To address the weight coupling problem, certain studies introduced few-shot Neural Architecture Search (NAS) methods, which partition the supernet into multiple sub-supernets. Howe…
Efficient Heuristics Generation for Solving Combinatorial Optimization Problems Using Large Language Models
Xuan Wu, Di Wang, Chunguo Wu +4
Recent studies exploited Large Language Models (LLMs) to autonomously generate heuristics for solving Combinatorial Optimization Problems (COPs), by prompting LLMs to first provide…
GELD: A Unified Neural Model for Efficiently Solving Traveling Salesman Problems Across Different Scales
Yubin Xiao, Di Wang, Rui Cao +3
The Traveling Salesman Problem (TSP) is a well-known combinatorial optimization problem with broad real-world applications. Recent advancements in neural network-based TSP solvers…