6 citations · 14 across the 11 of their papers we have counts for
8 papers · 1 filter
Online Automated Algorithm Design with Large Language Models
Zhiyao Zhang, Yichen Li, Xingyu Wu +2
Large language models (LLMs) enable automated algorithm design (AAD) through reasoning and code synthesis. However, most existing LLM-based AAD methods separate algorithm design fr…
Semantics-Aware Bilevel Co-Evolution: Towards Automated Multicomponent Algorithm Design
Zhiyao Zhang, Shenghao Wu, Xingyu Wu +1
LLM-assisted evolutionary search (LES) has emerged as a promising paradigm for automated algorithm design. However, existing methods usually suffer from two inherent limitations wh…
A Theoretical Analysis of Analogy-Based Evolutionary Transfer Optimization
Xiaoming Xue, Liang Feng, Yinglan Feng +3
Evolutionary transfer optimization (ETO) has been gaining popularity in research over the years due to its outstanding knowledge transfer ability to address various challenges in o…
Surrogate-Assisted Search with Competitive Knowledge Transfer for Expensive Optimization
Xiaoming Xue, Yao Hu, Liang Feng +3
Expensive optimization problems (EOPs) have attracted increasing research attention over the decades due to their ubiquity in a variety of practical applications. Despite many soph…
Learning to Transfer for Evolutionary Multitasking
Sheng-Hao Wu, Yuxiao Huang, Xingyu Wu +3
Evolutionary multitasking (EMT) is an emerging approach for solving multitask optimization problems (MTOPs) and has garnered considerable research interest. The implicit EMT is a s…
Large Language Model-Aided Evolutionary Search for Constrained Multiobjective Optimization
Zeyi Wang, Songbai Liu, Jianyong Chen +1
Evolutionary algorithms excel in solving complex optimization problems, especially those with multiple objectives. However, their stochastic nature can sometimes hinder rapid conve…
Towards Multi-Objective High-Dimensional Feature Selection via Evolutionary Multitasking
Yinglan Feng, Liang Feng, Songbai Liu +2
Evolutionary Multitasking (EMT) paradigm, an emerging research topic in evolutionary computation, has been successfully applied in solving high-dimensional feature selection (FS) p…
Multi-Space Evolutionary Search for Large-Scale Optimization
Liang Feng, Qingxia Shang, Yaqing Hou +2
In recent years, to improve the evolutionary algorithms used to solve optimization problems involving a large number of decision variables, many attempts have been made to simplify…