Suchergebnisse - expensive multi-objective (evolutionary OR evolution) algorithm*

Surrogate-assisted evolutionary algorithm with decomposition-based local learning for high-dimensional multi-objective optimization von 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 von 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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A pairwise comparison based surrogate-assisted evolutionary algorithm for expensive multi-objective optimization von 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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SEAMS: A surrogate-assisted evolutionary algorithm with metric-based dynamic strategy for expensive multi-objective optimization von 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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A classification surrogate-assisted multi-objective evolutionary algorithm for expensive optimization von 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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An efficient dominance decomposition-based deep graph evolutionary algorithm for the expensive multi-objective optimization von 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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Multi-objective multi-criteria evolutionary algorithm for multi-objective multi-task optimization von 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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Complementary surrogate-assisted differential evolution algorithm for expensive multi-objective problems under a limited computational budget von 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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Multiple surrogates-assisted evolutionary algorithm for high-dimensional expensive multi-objective optimization with adaptive diffusion map von 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 von 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 von 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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Expensive constrained multi-objective optimization via adaptive surrogate-assisted dense weight multi-objective evolutionary algorithm von 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 special point-guided surrogate-assisted multi-objective evolutionary algorithm for complex pareto fronts von 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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A comparison-relationship-surrogate evolutionary algorithm for multi-objective optimization von 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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Kriging-assisted indicator-based evolutionary algorithm for expensive multi-objective optimization von Li, Fei, Yang, Yujie, Shang, Zhengkun, Li, Siyuan, Ouyang, Haibin

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Solution of constrained mixed‐integer multi‐objective optimal power flow problem considering the hybrid multi‐objective evolutionary algorithm von 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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Surrogate-assisted operator-repeated evolutionary algorithm for computationally expensive multi-objective problems von Cai, Xiwen, Zou, Tao, Gao, Liang

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An adaptive Bayesian approach to surrogate-assisted evolutionary multi-objective optimization von 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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PRETTY: A parallel transgenerational learning-assisted evolutionary algorithm for computationally expensive multi-objective optimization von 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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Surrogate-assisted MOEA/D for expensive constrained multi-objective optimization von 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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