52 citations · 105 across the 18 of their papers we have counts for
22 papers · 1 filter
Quality-Diversity Optimization as Multi-Objective Optimization
Xi Lin, Ping Guo, Yilu Liu +2
The Quality-Diversity (QD) optimization aims to discover a collection of high-performing solutions that simultaneously exhibit diverse behaviors within a user-defined behavior spac…
EvoEngineer: Mastering Automated CUDA Kernel Code Evolution with Large Language Models
Ping Guo, Chenyu Zhu, Siyuan Chen +4
CUDA kernel optimization has become a critical bottleneck for AI performance, as deep learning training and inference efficiency directly depends on highly optimized GPU kernels. D…
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…
FoMEMO: Towards Foundation Models for Expensive Multi-objective Optimization
Yiming Yao, Fei Liu, Liang Zhao +3
Expensive multi-objective optimization is a prevalent and crucial concern in many real-world scenarios, where sample-efficiency is vital due to the limited evaluations to recover t…
Fine-tuning Large Language Model for Automated Algorithm Design
Fei Liu, Rui Zhang, Xi Lin +2
The integration of large language models (LLMs) into automated algorithm design has shown promising potential. A prevalent approach embeds LLMs within search routines to iterativel…
Learning to Insert for Constructive Neural Vehicle Routing Solver
Fu Luo, Xi Lin, Mengyuan Zhong +4
Neural Combinatorial Optimisation (NCO) is a promising learning-based approach for solving Vehicle Routing Problems (VRPs) without extensive manual design. While existing construct…