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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

A twofold infill criterion-driven heterogeneous ensemble surrogate-assisted evolutionary algorithm for computationally expensive problems
Mingyuan Yu, Jing Liang, Zhou Wu, et al.
Knowledge-Based Systems (2021) Vol. 236, pp. 107747-107747
Closed Access | Times Cited: 21

Showing 21 citing articles:

Evolutionary Optimization Methods for High-Dimensional Expensive Problems: A Survey
MengChu Zhou, Meiji Cui, Dian Xu, et al.
IEEE/CAA Journal of Automatica Sinica (2024) Vol. 11, Iss. 5, pp. 1092-1105
Closed Access | Times Cited: 18
Evolutionary Algorithms for Parameter Optimization—Thirty Years Later
Thomas Bäck, Anna V. Kononova, Bas van Stein, et al.
Evolutionary Computation (2023) Vol. 31, Iss. 2, pp. 81-122
Open Access | Times Cited: 35
A multi-strategy surrogate-assisted competitive swarm optimizer for expensive optimization problems
Jeng‐Shyang Pan, Qingwei Liang, Shu‐Chuan Chu, et al.
Applied Soft Computing (2023) Vol. 147, pp. 110733-110733
Closed Access | Times Cited: 16
Surrogate-assisted PSO with archive-based neighborhood search for medium-dimensional expensive multi-objective problems
Mingyuan Yu, Zhou Wu, Jing Liang, et al.
Information Sciences (2024) Vol. 666, pp. 120405-120405
Closed Access | Times Cited: 4
Swarm Intelligence-Based Evolutionary Machine Learning
Jing Liang, Kunjie Yu, Ying Bi, et al.
Elsevier eBooks (2025)
Closed Access
Adaptive surrogate-assisted multi-objective evolutionary algorithm using an efficient infill technique
Mengtian Wu, Lingling Wang, Jin Xu, et al.
Swarm and Evolutionary Computation (2022) Vol. 75, pp. 101170-101170
Closed Access | Times Cited: 19
Ensemble of surrogates in black-box-type engineering optimization: Recent advances and applications
Hao Chen, Zhilang Zhang, Weikun Li, et al.
Expert Systems with Applications (2024) Vol. 248, pp. 123427-123427
Closed Access | Times Cited: 3
Surrogate-assisted evolutionary algorithm with hierarchical surrogate technique and adaptive infill strategy
Hao Chen, Weikun Li, Weicheng Cui
Expert Systems with Applications (2023) Vol. 232, pp. 120826-120826
Closed Access | Times Cited: 10
A hierarchical surrogate assisted optimization algorithm using teaching-learning-based optimization and differential evolution for high-dimensional expensive problems
Jian Zhang, Muxi Li, Xinxin Yue, et al.
Applied Soft Computing (2023) Vol. 152, pp. 111212-111212
Closed Access | Times Cited: 8
Contrastive Learning: An Alternative Surrogate for Offline Data-Driven Evolutionary Computation
Hao-Gan Huang, Yue‐Jiao Gong
IEEE Transactions on Evolutionary Computation (2022) Vol. 27, Iss. 2, pp. 370-384
Closed Access | Times Cited: 12
A survey of surrogate-assisted evolutionary algorithms for expensive optimization
Jing Liang, Yahang Lou, Mingyuan Yu, et al.
Journal of Membrane Computing (2024)
Closed Access | Times Cited: 2
A Many-objective Ensemble Optimization Algorithm for the Edge Cloud Resource Scheduling Problem
Jiangjiang Zhang, Zhenhu Ning, Raja Hashim Ali, et al.
IEEE Transactions on Mobile Computing (2023), pp. 1-18
Open Access | Times Cited: 6
A framework of global exploration and local exploitation using surrogates for expensive optimization
Caie Hu, Sanyou Zeng, Changhe Li
Knowledge-Based Systems (2023) Vol. 280, pp. 111018-111018
Closed Access | Times Cited: 5
Data-driven Surrogate-assisted Method for High-dimensional Multi-area Combined Economic/Emission Dispatch
Chenhao Lin, Huijun Liang, Aokang Pang, et al.
Journal of Modern Power Systems and Clean Energy (2024) Vol. 12, Iss. 1, pp. 52-64
Open Access | Times Cited: 1
A Q-learning driven competitive surrogate assisted evolutionary optimizer with multiple oriented mutation operators for expensive problems
Qinna Zhu, Haibo Yu, Kang Li, et al.
Information Sciences (2024) Vol. 682, pp. 121224-121224
Closed Access | Times Cited: 1
Adaptive multi-surrogate and module-based optimization algorithm for high-dimensional and computationally expensive problems
Mengtian Wu, Jin Xu, Lingling Wang, et al.
Information Sciences (2023) Vol. 645, pp. 119308-119308
Closed Access | Times Cited: 4
Accelerated Parameter Tuning of Antenna Structures by Means of Response Features and Principal Directions
Anna Pietrenko‐Dabrowska, Sławomir Kozieł
IEEE Transactions on Antennas and Propagation (2023) Vol. 71, Iss. 11, pp. 8987-8999
Closed Access | Times Cited: 4
Surrogate-assisted Differential Evolution with Adaptation of Training Data Selection Criterion
Kei Nishihara, Masaya Nakata
2021 IEEE Symposium Series on Computational Intelligence (SSCI) (2022), pp. 1675-1682
Closed Access | Times Cited: 3
A Multi-Surrogate Assisted Multi-Tasking Optimization Algorithm for High-Dimensional Expensive Problems
Hongyu Li, Lei Chen, Jian Zhang, et al.
Algorithms (2024) Vol. 18, Iss. 1, pp. 4-4
Open Access
A Novel Alternate Point-taking Strategy for Surrogate-Assisted Evolutionary Algorithm
Muxi Li, Jiliang Zhang
Journal of Advances in Mathematics and Computer Science (2023) Vol. 38, Iss. 7, pp. 181-188
Open Access
A Historical Surrogate Model Ensemble Assisted Bayesian Evolutionary Optimization Algorithm for Solving Expensive Many-Objective Problems
Hui Liu, Jie Tian, Qian Yu, et al.
(2023)
Closed Access
Cost-Efficient Two-Level Modeling of Microwave Passives Using Feature-Based Surrogates and Domain Confinement
Anna Pietrenko‐Dabrowska, Sławomir Kozieł, Qi‐Jun Zhang
Electronics (2023) Vol. 12, Iss. 17, pp. 3560-3560
Open Access
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