Search Results - Expensive multi-objective evolutionary algorithm

A pairwise comparison based surrogate-assisted evolutionary algorithm for expensive multi-objective optimization by 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 expensive multi-objective evolutionary algorithm based on grid and relation learning by 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 classification surrogate-assisted multi-objective evolutionary algorithm for expensive optimization by 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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A data augmentation based Kriging-assisted reference vector guided evolutionary algorithm for expensive dynamic multi-objective optimization by Liu, Zhening, Wang, Handing

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A Review of Multi-Satellite Imaging Mission Planning Based on Surrogate Model Expensive Multi-Objective Evolutionary Algorithms: The Latest Developments and Future Trends by Yang, Xueying, Hu, Min, Huang, Gang, Lin, Peng, Wang, Yijun

“… response times for traditional algorithms. Surrogate model expensive multi-objective evolutionary algorithms (SM-EMOEAs…”
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Kriging-assisted indicator-based evolutionary algorithm for expensive multi-objective optimization by Li, Fei, Yang, Yujie, Shang, Zhengkun, Li, Siyuan, Ouyang, Haibin

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Regularity model based offspring generation in surrogate-assisted evolutionary algorithms for expensive multi-objective optimization by Li, Bingdong, Lu, Yongfan, Qian, Hong, Hong, Wenjing, Yang, Peng, Zhou, Aimin

“…Evolutionary algorithms face significant challenges when it comes to solving expensive multi-objective optimization problems, which require costly evaluations…”
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Accelerating surrogate assisted evolutionary algorithms for expensive multi-objective optimization via explainable machine learning by Li, Bingdong, Yang, Yanting, Liu, Dacheng, Zhang, Yan, Zhou, Aimin, Yao, Xin

“…A series of surrogate-assisted evolutionary algorithms (SAEAs) have been proposed to handle expensive multi-objective optimization problems (EMOPs…”
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An efficient dominance decomposition-based deep graph evolutionary algorithm for the expensive multi-objective optimization by 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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Neighborhood samples and surrogate assisted multi-objective evolutionary algorithm for expensive many-objective optimization problems by Zhao, Yi, Zeng, Jianchao, Tan, Ying

“…Many surrogate-assisted meta-heuristic algorithms have been proposed for single-objective expensive optimization problems, however, not so much attention has been paid to multi-objective expensive…”
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A bagging-based surrogate-assisted evolutionary algorithm for expensive multi-objective optimization by Liu, Yuanchao, Liu, Jianchang, Tan, Shubin, Yang, Yongkuan, Li, Fei

“…It is a big challenge for multi-objective evolutionary algorithms to solve expensive multi-objective optimization due to high computational cost…”
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Regression and relation-assisted evolutionary algorithm for high-dimensional expensive multi-objective optimization by Zhu, Shuwei, Zhang, Yimo, Fang, Wei, Cui, Meiji, Deb, Kalyanmoy

“…Surrogate-assisted evolutionary algorithms (SAEAs) have gained a lot of attention to handle expensive multi-objective optimization problems (EMOPs…”
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Surrogate-assisted operator-repeated evolutionary algorithm for computationally expensive multi-objective problems by Cai, Xiwen, Zou, Tao, Gao, Liang

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PRETTY: A parallel transgenerational learning-assisted evolutionary algorithm for computationally expensive multi-objective optimization by 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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The IGD+ indicator based evolutionary algorithm for expensive multi-objective optimization problems by Li, Fei, Shen, Hao, Wang, Yudong, Dai, Mingcheng, Park, Ju H.

“…Due to the high experimental cost in function evaluation procedure, commonly used evolutionary algorithms are difficult to solve expensive multi-objective optimization problems…”
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Multiple surrogates-assisted evolutionary algorithm for high-dimensional expensive multi-objective optimization with adaptive diffusion map by 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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Surrogate-assisted evolutionary algorithm for expensive constrained multi-objective discrete optimization problems by Gu, Qinghua, Wang, Qian, Xiong, Neal N., Jiang, Song, Chen, Lu

“… However, relatively little work has been dedicated to addressing expensive constrained multi-objective discrete optimization problems although there are many such problems in the real world…”
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A clustering-based surrogate-assisted evolutionary algorithm (CSMOEA) for expensive multi-objective optimization by Wang, Wenxin, Dong, Huachao, Wang, Peng, Wang, Xinjing, Shen, Jiangtao

“…This paper presents a novel surrogate-assisted evolutionary algorithm, CSMOEA, for multi-objective optimization problems (MOPs…”
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A population-oriented hybrid search surrogate-assisted evolutionary algorithm for expensive constrained optimization multi-objective problems with small feasible regions by Zhu, Cong, Yang, Yongkuan, Kong, Xiangsong, Li, Wenji

“…Multi-objective optimization problems with expensive objectives and constraints frequently arise in real industries, such problems are called expensive constrained multi-objective optimization problems(ECMOPs…”
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A data-driven co-evolutionary exploration algorithm for computationally expensive constrained multi-objective problems by 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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