Suchergebnisse - "IEEE transactions on evolutionary computation"

One Pixel Attack for Fooling Deep Neural Networks von Su, Jiawei, Vargas, Danilo Vasconcellos, Sakurai, Kouichi

“… Recent research has revealed that the output of deep neural networks (DNNs) can be easily altered by adding relatively small perturbations to the input vector …”
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A Survey on Evolutionary Constrained Multiobjective Optimization von Liang, Jing, Ban, Xuanxuan, Yu, Kunjie, Qu, Boyang, Qiao, Kangjia, Yue, Caitong, Chen, Ke, Tan, Kay Chen

“… Handling constrained multiobjective optimization problems (CMOPs) is extremely challenging, since multiple conflicting objectives subject to various …”
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A Coevolutionary Framework for Constrained Multiobjective Optimization Problems von Tian, Ye, Zhang, Tao, Xiao, Jianhua, Zhang, Xingyi, Jin, Yaochu

“… Constrained multiobjective optimization problems (CMOPs) are challenging because of the difficulty in handling both multiple objectives and constraints. While …”
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Evolving Deep Convolutional Neural Networks for Image Classification von Sun, Yanan, Xue, Bing, Zhang, Mengjie, Yen, Gary G.

“… Evolutionary paradigms have been successfully applied to neural network designs for two decades. Unfortunately, these methods cannot scale well to the modern …”
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A Review on Bilevel Optimization: From Classical to Evolutionary Approaches and Applications von Sinha, Ankur, Malo, Pekka, Deb, Kalyanmoy

“… Bilevel optimization is defined as a mathematical program, where an optimization problem contains another optimization problem as a constraint. These problems …”
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Two-Archive Evolutionary Algorithm for Constrained Multiobjective Optimization von Li, Ke, Chen, Renzhi, Fu, Guangtao, Yao, Xin

“… When solving constrained multiobjective optimization problems, an important issue is how to balance convergence, diversity, and feasibility simultaneously. To …”
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Data-Driven Evolutionary Optimization: An Overview and Case Studies von Jin, Yaochu, Wang, Handing, Chugh, Tinkle, Guo, Dan, Miettinen, Kaisa

“… Most evolutionary optimization algorithms assume that the evaluation of the objective and constraint functions is straightforward. In solving many real-world …”
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A Survey on the Hypervolume Indicator in Evolutionary Multiobjective Optimization von Shang, Ke, Ishibuchi, Hisao, He, Linjun, Pang, Lie Meng

“… Hypervolume is widely used as a performance indicator in the field of evolutionary multiobjective optimization (EMO). It is used not only for performance …”
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A Kriging-Assisted Two-Archive Evolutionary Algorithm for Expensive Many-Objective Optimization von Song, Zhenshou, Wang, Handing, He, Cheng, Jin, Yaochu

“… Only a small number of function evaluations can be afforded in many real-world multiobjective optimization problems (MOPs) where the function evaluations are …”
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An Evolutionary Algorithm for Large-Scale Sparse Multiobjective Optimization Problems von Tian, Ye, Zhang, Xingyi, Wang, Chao, Jin, Yaochu

“… In the last two decades, a variety of different types of multiobjective optimization problems (MOPs) have been extensively investigated in the evolutionary …”
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Multifactorial Evolutionary Algorithm With Online Transfer Parameter Estimation: MFEA-II von Bali, Kavitesh Kumar, Ong, Yew-Soon, Gupta, Abhishek, Tan, Puay Siew

“… Humans rarely tackle every problem from scratch. Given this observation, the motivation for this paper is to improve optimization performance through adaptive …”
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IGD Indicator-Based Evolutionary Algorithm for Many-Objective Optimization Problems von Sun, Yanan, Yen, Gary G., Yi, Zhang

“… Inverted generational distance (IGD) has been widely considered as a reliable performance indicator to concurrently quantify the convergence and diversity of …”
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Variable-Size Cooperative Coevolutionary Particle Swarm Optimization for Feature Selection on High-Dimensional Data von Song, Xian-Fang, Zhang, Yong, Guo, Yi-Nan, Sun, Xiao-Yan, Wang, Yong-Li

“… Evolutionary feature selection (FS) methods face the challenge of "curse of dimensionality" when dealing with high-dimensional data. Focusing on this …”
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An Indicator-Based Multiobjective Evolutionary Algorithm With Reference Point Adaptation for Better Versatility von Tian, Ye, Cheng, Ran, Zhang, Xingyi, Cheng, Fan, Jin, Yaochu

“… During the past two decades, a variety of multiobjective evolutionary algorithms (MOEAs) have been proposed in the literature. As pointed out in some recent …”
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A Survey of Automatic Parameter Tuning Methods for Metaheuristics von Huang, Changwu, Li, Yuanxiang, Yao, Xin

“… Parameter tuning, that is, to find appropriate parameter settings (or configurations) of algorithms so that their performance is optimized, is an important …”
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A Multiobjective Particle Swarm Optimizer Using Ring Topology for Solving Multimodal Multiobjective Problems von Yue, Caitong, Qu, Boyang, Liang, Jing

“… This paper presents a new particle swarm optimizer for solving multimodal multiobjective optimization problems which may have more than one Pareto-optimal …”
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A Survey on Evolutionary Computation Approaches to Feature Selection von Bing Xue, Mengjie Zhang, Browne, Will N., Xin Yao

“… Feature selection is an important task in data mining and machine learning to reduce the dimensionality of the data and increase the performance of an …”
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A Review on Evolutionary Multitask Optimization: Trends and Challenges von Wei, Tingyang, Wang, Shibin, Zhong, Jinghui, Liu, Dong, Zhang, Jun

“… Evolutionary algorithms (EAs) possess strong problem-solving abilities and have been applied in a wide range of applications. However, they still suffer from a …”
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Handling Constrained Multiobjective Optimization Problems With Constraints in Both the Decision and Objective Spaces von Liu, Zhi-Zhong, Wang, Yong

“… Constrained multiobjective optimization problems (CMOPs) are frequently encountered in real-world applications, which usually involve constraints in both the …”
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A Reference Vector Guided Evolutionary Algorithm for Many-Objective Optimization von Ran Cheng, Yaochu Jin, Olhofer, Markus, Sendhoff, Bernhard

“… In evolutionary multiobjective optimization, maintaining a good balance between convergence and diversity is particularly crucial to the performance of the …”
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