"Evolutionary computation"

Large-scale Multiobjective Optimization via Problem Decomposition and Reformulation
Large-scale multiobjective optimization problems (LSMOPs) are challenging for existing approaches due to the complexity of objective …
Lianghao Li, Cheng He, Ran Cheng, Linqiang Pan
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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
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Solving Many-Objective Optimization Problems via Multistage Evolutionary Search
With the increase in the number of optimization objectives, balancing the convergence and diversity in evolutionary multiobjective …
Huangke Chen, Ran Cheng, Witold Pedrycz, Yaochu Jin
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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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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
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Techniques for Accelerating Multi-Objective Evolutionary Algorithms in PlatEMO
It has been widely recognized that evolutionary computation is one of the most effective techniques for solving complex optimization …
Ye Tian, Ran Cheng, Xingyi Zhang, Yaochu Jin
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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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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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A Strengthened Dominance Relation Considering Convergence and Diversity for Evolutionary Many-Objective Optimization
Both convergence and diversity are crucial to evolutionary many-objective optimization, whereas most existing dominance relations show …
Ye Tian, Ran Cheng, Xingyi Zhang, Yansen Su, Yaochu Jin
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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
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