activity
20162021
most citedPreselection via Classification: A Case Study on Evolutionary Multiobjective Optimization

5 citations · 7 across the 3 of their papers we have counts for

collaborators

6 papers

cs.NE20211 cited

Variable Division and Optimization for Constrained Multiobjective Portfolio Problems

Yi Chen, Aimin Zhou

Variable division and optimization (D\&O) is a frequently utilized algorithm design paradigm in Evolutionary Algorithms (EAs). A D\&O EA divides a variable into partial variables a…

eess.IV20201 cited

Survey of the Detection and Classification of Pulmonary Lesions via CT and X-Ray

Yixuan Sun, Chengyao Li, Qian Zhang +2

In recent years, the prevalence of several pulmonary diseases, especially the coronavirus disease 2019 (COVID-19) pandemic, has attracted worldwide attention. These diseases can be…

eess.IV2020

Boundary Guidance Hierarchical Network for Real-Time Tongue Segmentation

Xinyi Zeng, Qian Zhang, Jia Chen +3

Automated tongue image segmentation in tongue images is a challenging task for two reasons: 1) there are many pathological details on the tongue surface, which affect the extractio…

cs.CE2019

Utilizing Dependence among Variables in Evolutionary Algorithms for Mixed-Integer Programming: A Case Study on Multi-Objective Constrained Portfolio Optimization

Yi Chen, Aimin Zhou, Swagatam Das

Several real-world applications could be modeled as Mixed-Integer Non-Linear Programming (MINLP) problems, and some prominent examples include portfolio optimization, remote sensin…

cs.NE20175 cited

Preselection via Classification: A Case Study on Evolutionary Multiobjective Optimization

Jinyuan Zhang, Aimin Zhou, Ke Tang +1

In evolutionary algorithms, a preselection operator aims to select the promising offspring solutions from a candidate offspring set. It is usually based on the estimated or real ob…

cs.NE2016

Learning from Non-Stationary Stream Data in Multiobjective Evolutionary Algorithm

Jianyong Sun, Hu Zhang, Aimin Zhou +1

Evolutionary algorithms (EAs) have been well acknowledged as a promising paradigm for solving optimisation problems with multiple conflicting objectives in the sense that they are…