Výsledky vyhľadávania - expensive multi-objective (evolutionary OR evolution) algorithm

Surrogate-assisted evolutionary algorithm with decomposition-based local learning for high-dimensional multi-objective optimization Autor Shen, Jiangtao, Wang, Peng, Dong, Huachao, Wang, Wenxin, Li, Jinglu

“…When the evolutionary algorithm is applied to handle high-dimensional expensive multi-objective optimization problems (MOPs…”
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Dual-space high-quality individual knowledge-driven surrogate-assisted multi-objective evolutionary algorithm with heterogeneous offspring generation Autor Bian, Xiaotong, Zhao, Feng, Liu, Hanqiang, Ning, Xinyi, Hu, Yikai

“…Surrogate-assisted multi-objective evolutionary algorithms have proven effective in solving expensive multi-objective optimization problems…”
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Multi-objective multi-criteria evolutionary algorithm for multi-objective multi-task optimization Autor Du, Ke-Jing, Li, Jian-Yu, Wang, Hua, Zhang, Jun

“…Evolutionary multi-objective multi-task optimization is an emerging paradigm for solving multi-objective multi-task optimization problem (MO-MTOP…”
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A pairwise comparison based surrogate-assisted evolutionary algorithm for expensive multi-objective optimization Autor Tian, Ye, Hu, Jiaxing, He, Cheng, Ma, Haiping, Zhang, Limiao, Zhang, Xingyi

“…Multi-objective optimization problems in many real-world applications are characterized by computationally or economically expensive objectives, which cannot provide sufficient function evaluations…”
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An adaptive Bayesian approach to surrogate-assisted evolutionary multi-objective optimization Autor Wang, Xilu, Jin, Yaochu, Schmitt, Sebastian, Olhofer, Markus

“…Surrogate models have been widely used for solving computationally expensive multi-objective optimization problems (MOPs…”
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SEAMS: A surrogate-assisted evolutionary algorithm with metric-based dynamic strategy for expensive multi-objective optimization Autor Liu, Haitao, Wang, Chia-Hung

“… formed by algorithms tends to be low. This paper proposes a metric-based surrogate-assisted evolutionary algorithm for multi-objective expensive optimization…”
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An efficient dominance decomposition-based deep graph evolutionary algorithm for the expensive multi-objective optimization Autor Cai, Xing, Zhang, Tong, Cui, Zhen

“… In this work, we propose a deep graph-based evolutionary algorithm, named the multi-objective evolutionary algorithm based on dominance decomposition and graph neural networks (MOEA-DDG…”
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A classification surrogate-assisted multi-objective evolutionary algorithm for expensive optimization Autor Li, Jinglu, Wang, Peng, Dong, Huachao, Shen, Jiangtao, Chen, Caihua

“…Surrogate-assisted multi-objective evolutionary algorithms (SAMOEAs) have been developed for solving expensive optimization problems…”
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Expensive constrained multi-objective optimization via adaptive surrogate-assisted dense weight multi-objective evolutionary algorithm Autor Liu, Jiansheng, Hu, Haoran, Liu, Zhiyong, Yang, Zan, Chen, Liming, Cai, Xiwen

“… This paper designs an adaptive surrogate-assisted dense weight multi-objective evolutionary algorithm (ASDWMOEA…”
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A comparison-relationship-surrogate evolutionary algorithm for multi-objective optimization Autor Pierce, Christopher M., Kim, Young-Kee, Bazarov, Ivan

“…Evolutionary algorithms often struggle to find well converged (e.g small inverted generational distance on test problems…”
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Complementary surrogate-assisted differential evolution algorithm for expensive multi-objective problems under a limited computational budget Autor Cai, Xiwen, Ruan, Gan, Yuan, Bo, Gao, Liang

“… By hybridizing two complementary surrogate-assisted strategies, this study proposed an efficient surrogate-assisted differential evolution algorithm to optimize expensive multi-objective problems…”
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Surrogate-assisted MOEA/D for expensive constrained multi-objective optimization Autor Yang, Zan, Qiu, Haobo, Gao, Liang, Chen, Liming, Liu, Jiansheng

“…) is proposed for solving computationally expensive constrained multi-objective optimization problems, in which three specific search strategies are adaptively implemented based on the optimization…”
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Multiple surrogates-assisted evolutionary algorithm for high-dimensional expensive multi-objective optimization with adaptive diffusion map Autor Yan, Zeyuan, Zhou, Yuren, Su, Chupeng, Tan, Yanyan

“…Surrogate-assisted evolutionary algorithms (SAEAs) have made significant progress in solving expensive multi/many-objective optimization problems…”
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A data-driven co-evolutionary exploration algorithm for computationally expensive constrained multi-objective problems Autor Long, Wenyi, Wang, Peng, Dong, Huachao, Li, Jinglu, Fu, Chongbo

“…Surrogate-assisted multi-objective optimization algorithms have attracted widespread attention due to their outstanding performance in computationally expensive real-world problems…”
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An expensive multi-objective evolutionary algorithm based on grid and relation learning Autor Cheng, Yan, Wang, Jiaqi, Yu, Gongcheng, Yao, Yuxiao, Chen, Yanyin, Li, Guowei

“… The evaluation process consumes computational resources or funds, making it difficult to provide adequate function evaluations for converging evolutionary algorithms…”
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A special point-guided surrogate-assisted multi-objective evolutionary algorithm for complex pareto fronts Autor He, Chunlin, Zhang, Yong, Gong, Dunwei, Sun, Xianyan, Wang, Hongfeng

“…Expensive multi-objective optimization problems (EMOPs) with complex Pareto fronts are widespread in engineering design applications…”
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Kriging-assisted indicator-based evolutionary algorithm for expensive multi-objective optimization Autor Li, Fei, Yang, Yujie, Shang, Zhengkun, Li, Siyuan, Ouyang, Haibin

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Surrogate-assisted operator-repeated evolutionary algorithm for computationally expensive multi-objective problems Autor Cai, Xiwen, Zou, Tao, Gao, Liang

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PRETTY: A parallel transgenerational learning-assisted evolutionary algorithm for computationally expensive multi-objective optimization Autor Zou, Mingyin, Zhu, Xiaomin, Tian, Ye, Wang, Ji, Chen, Huangke

“…Many real-world optimization problems, called computationally expensive optimization problems, often require a time-consuming fitness evaluation through computer simulation or neural network training…”
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Solution of constrained mixed‐integer multi‐objective optimal power flow problem considering the hybrid multi‐objective evolutionary algorithm Autor Ali, Aamir, Abbas, Ghulam, Keerio, Muhammad Usman, Koondhar, Mohsin Ali, Chandni, Kiran, Mirsaeidi, Sohrab

“…An Optimal power flow (OPF) is non‐linear and constrained multi‐objective problem. OPF problems are expensive and evolutionary algorithms…”
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