evolutionary computation

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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Lamarckian Platform: Pushing the Boundaries of Evolutionary Reinforcement Learning Towards Asynchronous Commercial Games
Despite the emerging progress of integrating evolutionary computation into reinforcement learning, the absence of a high-performance …
Hui Bai, Ruimin Shen, Yue Lin, Botian Xu, Ran Cheng
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Reference Vector-Assisted Adaptive Model Management for Surrogate-Assisted Many-Objective Optimization
Acquisition functions for surrogate-assisted many-objective optimization require a delicate balance between convergence and diversity. …
Qiqi Liu, Ran Cheng, Yaochu Jin, Martin Heiderich, Tobias Rodemann
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Evolutionary Large-Scale Multi-Objective Optimization: A Survey
Multi-objective evolutionary algorithms (MOEAs) have shown promising performance in solving various optimization problems, but their …
Ye Tian, Langchun Si, Xingyi Zhang, Ran Cheng, Cheng He, Kay Chen Tan, Yaochu Jin
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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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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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