2 citations · 2 across the 4 of their papers we have counts for
17 papers
Hyper-ES: Effective Evolution Strategies for LLM Reasoning via Descent Direction Merging
Yu Gu, Zhi Zheng, Yunpeng Ba +3
Evolution Strategy (ES) is a promising alternative to gradient-based fine-tuning for resource-constrained Large Language Model (LLM) reasoning. However, directly applying ES to bil…
Instance-Conditioned Adaptation for Large-scale Generalization of Neural Routing Solver
Changliang Zhou, Xi Lin, Zhenkun Wang +3
In modern intelligent transportation systems (ITS), particularly in freight transportation and logistics, real-time route planning is crucial. It presents unique challenges driven…
Enhancing CVRP Solver through LLM-driven Automatic Heuristic Design
Zhuoliang Xie, Fei Liu, Zhenkun Wang +1
The Capacitated Vehicle Routing Problem (CVRP), a fundamental combinatorial optimization challenge, focuses on optimizing fleet operations under vehicle capacity constraints. While…
Learning to Reduce Search Space for Generalizable Neural Routing Solver
Changliang Zhou, Xi Lin, Zhenkun Wang +1
Constructive neural combinatorial optimization (NCO) offers a promising paradigm for solving vehicle routing problems (VRPs) by directly learning to construct approximate optimal s…
URS: A Unified Neural Routing Solver for Cross-Problem Zero-Shot Generalization
Changliang Zhou, Canhong Yu, Shunyu Yao +4
Multi-task neural routing solvers have emerged as a promising paradigm for their ability to solve multiple vehicle routing problems (VRPs) using a single model. However, existing n…
Survey on Neural Routing Solvers
Yunpeng Ba, Xi Lin, Changliang Zhou +7
Neural routing solvers (NRSs) that leverage deep learning to tackle vehicle routing problems have demonstrated notable potential for practical applications. By learning implicit he…