Suchergebnisse - Learnable evolutionary algorithms

A Survey on Learnable Evolutionary Algorithms for Scalable Multiobjective Optimization von Liu, Songbai, Lin, Qiuzhen, Li, Jianqiang, Tan, Kay Chen

“… Recent decades have witnessed great advancements in multiobjective evolutionary algorithms (MOEAs …”
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Testing vision-based control systems using learnable evolutionary algorithms von Abdessalem, Raja Ben, Nejati, Shiva, Briand, Lionel C., Stifter, Thomas

“… Testing such systems is complicated by complex and multidimensional input spaces. We propose an automated testing algorithm that builds on learnable evolutionary algorithms …”
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Learning to Learn Evolutionary Algorithm: A Learnable Differential Evolution von Liu, Xin, Sun, Jianyong, Zhang, Qingfu, Wang, Zhenkun, Xu, Zongben

“… With the advancement of artificial intelligence, especially deep learning and reinforcement learning, it is becoming appealing to rethink the design and development of evolutionary algorithm (EA …”
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Sequential Learnable Evolutionary Algorithm: A Research Program von Shiu Yin Yuen, Xin Zhang, Yang Lou

“… Evolutionary algorithms are typically run several times in design optimization problems and the best solution taken …”
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Multi-Station Agricultural Machinery Scheduling Based on Spatiotemporal Clustering and Learnable Multi-Objective Evolutionary Algorithm von Jia, Liruizhi, Zhang, Qinshuo, Liu, Shengquan, Kong, Bo, Liu, Yuan

“… Multi-objective evolutionary algorithms are sensitive to the initial population quality and local search strategies for path planning, where unreasonable initial solutions or improper local search …”
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A Survey on Learnable Evolutionary Algorithms for Scalable Multiobjective Optimization von Liu, Songbai, Lin, Qiuzhen, Li, Jianqiang, Kay Chen Tan

“… Recent decades have witnessed great advancements in multiobjective evolutionary algorithms (MOEAs …”
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An analysis of a model-based evolutionary algorithm: Learnable Evolution Model von Coletti, Mark

“… Learnable Evolution Model (LEM) is an EA that has an evolutionary algorithm component that works in tandem with a machine learner to collaboratively create populations of individuals …”
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A Federated Data-driven Multiobjective Evolutionary Algorithm via Continual Learnable Clustering von Kinoshita, Takato, Masuyama, Naoki, Nojima, Yusuke

“… However, to the best of our knowledge, a few studies tackle this emerging topic. This paper introduces multiobjective evolutionary algorithms (MOEAs …”
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Learning improvement representations to accelerate evolutionary large-scale multiobjective optimization von Liu, Songbai, Wang, Zeyi, Ma, Lijia, Chen, Jianyong, Zhou, Xun

“… Large-Scale multi-objective optimization problems present significant challenges to traditional evolutionary algorithms due to the exponentially increased search space and computational burden …”
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Multi-objective mobile robot path planning problem through learnable evolution model von Moradi, Behzad

“… A new multi-objective non-Darwinian-type evolutionary computation approach based on learnable evolution model (LEM …”
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Meta-MOGA: Meta-learning Multi-Objective Genetic Algorithm von Li, Tianyu, Wu, Kai, Li, Xiaobin, Teng, Xiangyi, Liu, Jing

“… However, these learnable evolutionary algorithms are only applicable to single-objective optimization and cannot be applied to multi-objective optimization problems …”
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Learnable Evolutionary Multi-Objective Combinatorial Optimization via Sequence-to-Sequence Model von Huang, Jiaxiang, Jiao, Licheng

“… Recent advances in learnable evolutionary algorithms have demonstrated the importance of leveraging population distribution information and historical evolutionary trajectories …”
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Learnable Evolutionary Search Across Heterogeneous Problems via Kernelized Autoencoding von Zhou, Lei, Feng, Liang, Gupta, Abhishek, Ong, Yew-Soon

“… The design of the evolutionary algorithm with learning capability from past search experiences has attracted growing research interests in recent years …”
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A New Automated Design Method Based on Machine Learning for CMOS Analog Circuits von Moradi, Behzad, Mirzaei, Abdolreza

“… A new simulation based automated CMOS analog circuit design method which applies a multi-objective non-Darwinian-type evolutionary algorithm based on Learnable Evolution Model (LEM …”
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An improved learnable evolution model for solving multi-objective vehicle routing problem with stochastic demand von Niu, Yunyun, Kong, Detian, Wen, Rong, Cao, Zhiguang, Xiao, Jianhua

“… ), due to the uncertainty in customer demands and potentially conflicted objectives. In this paper, we present an improved multi-objective learnable evolution model (IMOLEM …”
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A Learnable Prior Improves Inverse Tumor Growth Modeling von Weidner, Jonas, Ezhov, Ivan, Balcerak, Michal, Metz, Marie-Christin, Litvinov, Sergey, Kaltenbach, Sebastian, Feiner, Leonhard, Lux, Laurin, Kofler, Florian, Lipkova, Jana, Latz, Jonas, Rueckert, Daniel, Menze, Bjoern, Wiestler, Benedikt

“… Our method incorporates a DL ensemble for initial parameter estimation, facilitating efficient downstream evolutionary sampling initialized with this DL-based prior …”
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Boosting Adversarial Transferability With Learnable Patch-Wise Masks von Wei, Xingxing, Zhao, Shiji

“… To accurately localize these regions, we present a learnable approach to automatically optimize the mask …”
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The new optimization algorithm for the vehicle routing problem with time windows using multi-objective discrete learnable evolution model von Moradi, Behzad

“… (VRPTW). Learnable evolution model (LEM) includes a machine learning algorithm, like the decision trees, that can discover the correct directions of the evolution leading to significant improvements in the fitness of the individuals …”
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Reinforcement learning-assisted evolutionary algorithm: A survey and research opportunities von Song, Yanjie, Wu, Yutong, Guo, Yangyang, Yan, Ran, Suganthan, Ponnuthurai Nagaratnam, Zhang, Yue, Pedrycz, Witold, Das, Swagatam, Mallipeddi, Rammohan, Ajani, Oladayo Solomon, Feng, Qiang

“… Evolutionary algorithms (EA), a class of stochastic search methods based on the principles of natural evolution, have received widespread acclaim for their exceptional performance in various real-world optimization problems …”
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Multi-objective evolutionary algorithm based on RBF network for solving the stochastic vehicle routing problem von Niu, Yunyun, Shao, Jie, Xiao, Jianhua, Song, Wen, Cao, Zhiguang

“… Most multi-objective evolutionary algorithm dealing with this problem update current population without any guidance from previous searching experience …”
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