8 papers · 1 filter
OptGraph: Large Language Models Enhanced Evolutionary Optimization Via Graph Retrieval-Augmented Generation
Xianchao Xiu, Jianhao Li, Huangyue Chen +1
Large language models (LLMs) have emerged as a powerful tool for automated evolutionary optimization, but existing methods remain limited in pattern reuse, error-aware refinement,…
Vehicle Routing Problem Meets Large Language Models: An Overview and Perspectives
Xianchao Xiu, Chong Shen, Yanjiao Zhu +1
The vehicle routing problem (VRP) is a central optimization problem in artificial intelligence, logistics automation, transportation scheduling, and industrial decision-making. VRP…
Large Language Models for Operations Research: A Comprehensive Survey
Xianchao Xiu, Jianhao Li, Jun Fan +1
Operations Research (OR) serves as a core decision-support methodology for complex systems, with significant applications across mathematics, management science, and computer scien…
Compressed Proximal Federated Learning for Non-Convex Composite Optimization on Heterogeneous Data
Pu Qiu, Chen Ouyang, Yongyang Xiong +3
Federated Composite Optimization (FCO) has emerged as a promising framework for training models with structural constraints (e.g., sparsity) in distributed edge networks. However,…
Robust Sparse Phase Retrieval: Statistical Guarantee, Optimality Theory and Convergent Algorithm
Jun Fan, Ailing Yan, Xianchao Xiu +1
Phase retrieval (PR) is a popular research topic in signal processing and machine learning. However, its performance degrades significantly when the measurements are corrupted by n…
Sparse Tensor CCA via Manifold Optimization for Multi-View Learning
Yanjiao Zhu, Wanquan Liu, Xianchao Xiu +1
Tensor canonical correlation analysis (TCCA) has garnered significant attention due to its effectiveness in capturing high-order correlations in multi-view learning. However, exist…