Cheng He (何成)
Cheng He (何成)
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2021
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A Repository of Real-World Datasets for Data-Driven Evolutionary Multiobjective Optimization
DOI
Efficient evolutionary neural architecture search by modular inheritable crossover
Deep neural networks are widely used in the domain of image classification, and a large number of excellent deep neural networks have …
Cheng He
,
Hao Tan
,
Shihua Huang
,
Ran Cheng
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DOI
Paired Offspring Generation for Constrained Large-Scale Multiobjective Optimization
Constrained multiobjective optimization problems (CMOPs) widely exist in real-world applications, and they are challenging for …
Cheng He
,
Ran Cheng
,
Ye Tian
,
Xingyi Zhang
,
Kay Chen Tan
,
Yaochu Jin
Cite
DOI
Manifold Learning-Inspired Mating Restriction for Evolutionary Multiobjective Optimization With Complicated Pareto Sets
Under certain smoothness assumptions, the Pareto set of a continuous multiobjective optimization problem is a piecewise continuous …
Linqiang Pan
,
Lianghao Li
,
Ran Cheng
,
Cheng He
,
Kay Chen Tan
Cite
DOI
Evolutionary Multiobjective Optimization Driven by Generative Adversarial Networks (GANs)
Recently, increasing works have been proposed to drive evolutionary algorithms using machine-learning models. Usually, the performance …
Cheng He
,
Shihua Huang
,
Ran Cheng
,
Kay Chen Tan
,
Yaochu Jin
Cite
DOI
Adaptive dropout for high-dimensional expensive multiobjective optimization
Various works have been proposed to solve expensive multiobjective optimization problems (EMOPs) using surrogate-assisted evolutionary …
Jianqing Lin
,
Cheng He
,
Ran Cheng
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DOI
An inverse design method for supercritical airfoil based on conditional generative models
Inverse design has long been an efficient and powerful design tool in the aircraft industry. In this paper, a novel inverse design …
Jing Wang
,
Runze Li
,
Cheng He
,
Haixin Chen
,
Ran Cheng
,
Chen Zhai
,
Miao Zhang
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DOI
Adaptive simulated binary crossover for rotated multi-objective optimization
Crossover is a crucial operation for generating promising offspring solutions in evolutionary multi-objective optimization. Among …
Linqiang Pan
,
Wenting Xu
,
Lianghao Li
,
Cheng He
,
Ran Cheng
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DOI
RelativeNAS: Relative Neural Architecture Search via Slow-Fast Learning
Despite the remarkable successes of convolutional neural networks (CNNs) in computer vision, it is time-consuming and error-prone to …
Hao Tan
,
Ran Cheng
,
Shihua Huang
,
Cheng He
,
Changxiao Qiu
,
Fan Yang
,
Ping Luo
Cite
DOI
Population Sizing of Evolutionary Large-Scale Multiobjective Optimization
Large-scale multiobjective optimization problems (LSMOPs) are emerging and widely existed in real-world applications, which involve a …
Cheng He
,
Ran Cheng
Cite
DOI
Operator-Adapted Evolutionary Large-Scale Multiobjective Optimization for Voltage Transformer Ratio Error Estimation
Large-scale multiobjective optimization problems (LSMOPs) exist widely in real-world applications, and they are challenging for …
Changwu Huang
,
Lianghao Li
,
Cheng He
,
Ran Cheng
,
Xin Yao
Cite
DOI
Multi-objective Neural Architecture Search with Almost No Training
In the recent past, neural architecture search (NAS) has attracted increasing attention from both academia and industries. Despite the …
Shengran Hu
,
Ran Cheng
,
Cheng He
,
Zhichao Lu
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DOI
Manifold Learning Inspired Mating Restriction for Evolutionary Constrained Multiobjective Optimization
Lianghao Li
,
Cheng He
,
Ran Cheng
,
Linqiang Pan
Cite
Large-Scale Multiobjective Optimization via Problem Decomposition and Reformulation
Lianghao Li
,
Cheng He
,
Ran Cheng
,
Linqiang Pan
Cite
Dimension Dropout for Evolutionary High-Dimensional Expensive Multiobjective Optimization
In the past decades, a number of surrogate-assisted evolutionary algorithms (SAEAs) have been developed to solve expensive …
Jianqing Lin
,
Cheng He
,
Ran Cheng
Cite
DOI
Reformulating preferences into constraints for evolutionary multi- and many-objective optimization
Despite that the reference point based preference articulation plays a vital role in evolutionary multi- and many-objective …
Zhanglu Hou
,
Cheng He
,
Ran Cheng
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DOI
Evolutionary Large-Scale Multiobjective Optimization for Ratio Error Estimation of Voltage Transformers
Ratio error (RE) estimation of the voltage transformers (VTs) plays an important role in modern power delivery systems. Existing RE …
Cheng He
,
Ran Cheng
,
Chuanji Zhang
,
Ye Tian
,
Qin Chen
,
Xin Yao
Cite
DOI
Iterated Problem Reformulation for Evolutionary Large-Scale Multiobjective Optimization
Due to the curse of dimensionality, two main issues remain challenging for applying evolutionary algorithms (EAs) to large-scale …
Cheng He
,
Ran Cheng
,
Ye Tian
,
Xingyi Zhang
Cite
DOI
Constructing an automatic diagnosis and severity-classification model for acromegaly using facial photographs by deep learning
Due to acromegaly’s insidious onset and slow progression, its diagnosis is usually delayed, thus causing severe complications and …
Yanguo Kong
,
Xiangyi Kong
,
Cheng He
,
Changsong Liu
,
Liting Wang
,
Lijuan Su
,
Jun Gao
,
Qi Guo
,
Ran Cheng
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DOI
Guiding Evolutionary Multiobjective Optimization With Generic Front Modeling
In evolutionary multiobjective optimization, the Pareto front (PF) is approximated by using a set of representative candidate solutions …
Ye Tian
,
Xingyi Zhang
,
Ran Cheng
,
Cheng He
,
Yaochu Jin
Cite
DOI
Efficient Evolutionary Deep Neural Architecture Search (NAS) by Noisy Network Morphism Mutation
Deep learning has achieved enormous breakthroughs in the field of image recognition. However, due to the time-consuming and error-prone …
Yiming Chen
,
Tianci Pan
,
Cheng He
,
Ran Cheng
Cite
DOI
Adaptive Offspring Generation for Evolutionary Large-Scale Multiobjective Optimization
Offspring generation plays an important role in evolutionary multiobjective optimization. However, generating promising candidate …
Cheng He
,
Ran Cheng
,
Danial Yazdani
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DOI
Accelerating Large-Scale Multiobjective Optimization via Problem Reformulation
In this paper, we propose a framework to accelerate the computational efficiency of evolutionary algorithms on large-scale …
Cheng He
,
Lianghao Li
,
Ye Tian
,
Xingyi Zhang
,
Ran Cheng
,
Yaochu Jin
,
Xin Yao
Cite
DOI
Surrogate-Assisted Expensive Many-Objective Optimization by Model Fusion
Surrogate-assisted evolutionary algorithms have played an important role in expensive optimization where a small number of …
Cheng He
,
Ran Cheng
,
Yaochu Jin
,
Xin Yao
Cite
DOI
A Hybrid Surrogate-Assisted Evolutionary Algorithm for Computationally Expensive Many-Objective Optimization
Many real-world optimization problems are challenging because the evaluation of solutions is computationally expensive. As a result, …
Kanzhen Wan
,
Cheng He
,
Auraham Camacho
,
Ke Shang
,
Ran Cheng
,
Hisao Ishibuchi
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DOI
Efficient evolutionary neural architecture search (NAS) by modular inheritable crossover
Hao Tan
,
Cheng He
,
Dexuan Tang
,
Ran Cheng
Cite
A Multistage Evolutionary Algorithm for Better Diversity Preservation in Multiobjective Optimization
Diversity preservation is a crucial technique in multiobjective evolutionary algorithms (MOEAs), which aims at evolving the population …
Ye Tian
,
Cheng He
,
Ran Cheng
,
Xingyi Zhang
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DOI
Model-based evolutionary algorithms: a short survey
The evolutionary algorithms (EAs) are a family of nature-inspired algorithms widely used for solving complex optimization problems. …
Ran Cheng
,
Cheng He
,
Yaochu Jin
,
Xin Yao
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DOI
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