The DOI matches its Crossref record; 54 of the 54 references it cites were found in a registry or an index.
Surrogate-assisted evolutionary computation: Recent advances and future challenges
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Citations
Cites
Design and Analysis of Computer Experiments
Sacks, J., Welch, W. J., Mitchell, T. J., & Wynn, H. P. (1989) · Statistical Science · doi:10.1214/ss/1177012413 · Cited by 6,919
Engineering Design via Surrogate Modelling: A Practical Guide
Keane, A., Forrester, A., & Sobester, A. (2008) · American Institute of Aeronautics and Astronautics eBooks · doi:10.2514/4.479557 · Cited by 1,686
Evolutionary Optimization in Uncertain Environments—A Survey
Jin, Y., & Branke, J. (2005) · IEEE Transactions on Evolutionary Computation · doi:10.1109/tevc.2005.846356 · Cited by 1,572
Self-citationTakagi, H. (2001) · Proceedings of the IEEE · doi:10.1109/5.949485 · Cited by 1,327
Knowles, J. (2006) · IEEE Transactions on Evolutionary Computation · doi:10.1109/tevc.2005.851274 · Cited by 1,254
A comprehensive survey of fitness approximation in evolutionary computation
Jin, Y. (2005) · Soft Computing · doi:10.1007/s00500-003-0328-5 · Cited by 1,229
Self-citation(1991) · Lecture Notes in Computer Science · doi:10.1007/bfb0029723 · Cited by 1,049
Learn++: an incremental learning algorithm for supervised neural networks
Polikar, R., Upda, L., Upda, S. S., & Honavar, V. (2001) · IEEE Transactions on Systems, Man and Cybernetics, Part C (Applications and Reviews) · doi:10.1109/5326.983933 · Cited by 888
Single- and multiobjective evolutionary optimization assisted by Gaussian random field metamodels
Emmerich, M. T. M., Giannakoglou, K. C., & Naujoks, B. (2006) · IEEE Transactions on Evolutionary Computation · doi:10.1109/tevc.2005.859463 · Cited by 759
Expensive Multiobjective Optimization by MOEA/D With Gaussian Process Model
Zhang, Q., Liu, W., Tsang, E., & Virginas, B. (2010) · IEEE Transactions on Evolutionary Computation · doi:10.1109/tevc.2009.2033671 · Cited by 746
Cited by
A comprehensive survey: Whale Optimization Algorithm and its applications
Gharehchopogh, F. S., & Gholizadeh, H. (2019) · Swarm and Evolutionary Computation · doi:10.1016/j.swevo.2019.03.004 · Cited by 758
Bio-inspired computation: Where we stand and what's next
Del Ser, J., Osaba, E., Molina, D., Yang, X.-S., Salcedo-Sanz, S., Camacho, D., Das, S., Suganthan, P. N., Coello Coello, C. A., & Herrera, F. (2019) · Swarm and Evolutionary Computation · doi:10.1016/j.swevo.2019.04.008 · Cited by 593
Karimi-Mamaghan, M., Mohammadi, M., Meyer, P., Karimi-Mamaghan, A. M., & Talbi, E.-G. (2022) · European Journal of Operational Research · doi:10.1016/j.ejor.2021.04.032 · Cited by 462
Liu, H., Ong, Y.-S., & Cai, J. (2018) · Structural and Multidisciplinary Optimization · doi:10.1007/s00158-017-1739-8 · Cited by 444
Osaba, E., Villar-Rodriguez, E., Del Ser, J., Nebro, A. J., Molina, D., LaTorre, A., Suganthan, P. N., Coello Coello, C. A., & Herrera, F. (2021) · Swarm and Evolutionary Computation · doi:10.1016/j.swevo.2021.100888 · Cited by 406
Metadata
- Authors
- Jin, Y.
- Venue
- Swarm and Evolutionary Computation
- Publisher
- Elsevier BV
- Published
- 2011-06
- Volume
- 1
- Issue
- 2
- Pages
- 61-70
- ISSN
- 2210-6502 (ISSN-L)
- OpenAlex
- W2011174137
- Cited by
- 1,514
- References
- 54
- FWCI
- 27.51
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Surrogate-assisted evolutionary computation: Recent advances and future challenges. https://app.cochat.ai/papers/10.1016/j.swevo.2011.05.001
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- Jin, Y. (2011). Surrogate-assisted evolutionary computation: Recent advances and future challenges. Swarm and Evolutionary Computation. https://doi.org/10.1016/j.swevo.2011.05.001
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
