Optimization

Evolutionary Large-Scale Dynamic Optimization Using Bilevel Variable Grouping
Variable grouping provides an efficient approach to large-scale optimization, and multipopulation strategies are effective for both …
Hui Bai, Ran Cheng, Danial Yazdani, Kay Chen Tan, Yaochu Jin
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Large-scale Multiobjective Optimization via Reformulated Decision Variable Analysis
With the rising number of large-scale multiobjective optimization problems (LSMOPs) from academia and industries, some multiobjective …
Cheng He, Ran Cheng, Lianghao Li, Kay Chen Tan, Yaochu Jin
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Neural Architecture Search as Multiobjective Optimization Benchmarks: Problem Formulation and Performance Assessment
The ongoing advancements in network architecture design have led to remarkable achievements in deep learning across various challenging …
Zhichao Lu, Ran Cheng, Yaochu Jin, Kay Chen Tan, Kalyanmoy Deb
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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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RL-CSL: A Combinatorial Optimization Method Using Reinforcement Learning and Contrastive Self-Supervised Learning
Reinforcement learning-based methods have shown great potential in solving combinatorial optimization problems. However, the related …
Zhongju Yuan, Genghui Li, Zhenkun Wang, Jianyong Sun, Ran Cheng
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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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A Survey of Evolutionary Continuous Dynamic Optimization Over Two Decades—Part B
This article presents the second Part of a two-Part survey that reviews evolutionary dynamic optimization (EDO) for single-objective …
Danial Yazdani, Ran Cheng, Donya Yazdani, Jürgen Branke, Yaochu Jin, Xin Yao
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Efficient Evolutionary Search of Attention Convolutional Networks via Sampled Training and Node Inheritance
The performance of deep neural networks is heavily dependent on its architecture and various neural architecture search strategies have …
Haoyu Zhang, Yaochu Jin, Ran Cheng, Kuangrong Hao
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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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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
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