2 citations · 2 across the 6 of their papers we have counts for
10 papers · 1 filter
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…
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…
ARS: Automatic Routing Solver with Large Language Models
Kai Li, Fei Liu, Zhenkun Wang +4
Real-world Vehicle Routing Problems (VRPs) are characterized by a variety of practical constraints, making manual solver design both knowledge-intensive and time-consuming. Althoug…
Monte Carlo Tree Search for Comprehensive Exploration in LLM-Based Automatic Heuristic Design
Zhi Zheng, Zhuoliang Xie, Zhenkun Wang +1
Handcrafting heuristics for solving complex optimization tasks (e.g., route planning and task allocation) is a common practice but requires extensive domain knowledge. Recently, La…
LLM4AD: A Platform for Algorithm Design with Large Language Model
Fei Liu, Rui Zhang, Zhuoliang Xie +10
We introduce LLM4AD, a unified Python platform for algorithm design (AD) with large language models (LLMs). LLM4AD is a generic framework with modularized blocks for search methods…