36 citations · 42 across the 7 of their papers we have counts for
6 papers · 1 filter
Multi-Task Surrogate-Assisted Search with Bayesian Competitive Knowledge Transfer for Expensive Optimization
Yi Lu, Xiaoming Xue, Kai Zhang +5
Expensive optimization problems (EOPs) present significant challenges for traditional evolutionary optimization due to their limited evaluation calls. Although surrogate-assisted s…
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…
Rank-Based Learning and Local Model Based Evolutionary Algorithm for High-Dimensional Expensive Multi-Objective Problems
Guodong Chen, Jiu Jimmy Jiao, Xiaoming Xue +1
Surrogate-assisted evolutionary algorithms have been widely developed to solve complex and computationally expensive multi-objective optimization problems in recent years. However,…
A Scalable Test Problem Generator for Sequential Transfer Optimization
Xiaoming Xue, Cuie Yang, Liang Feng +3
Sequential transfer optimization (STO), which aims to improve the optimization performance on a task of interest by exploiting the knowledge captured from several previously-solved…
Data-driven evolutionary algorithm for oil reservoir well-placement and control optimization
Guodong Chen, Xin Luo, Jimmy Jiu Jiao +1
Optimal well placement and well injection-production are crucial for the reservoir development to maximize the financial profits during the project lifetime. Meta-heuristic algorit…