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Survey of multi-objective optimization methods for engineering
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Cited by
Collaborative Cloud and Edge Computing for Latency Minimization
Ren, J., Yu, G., He, Y., & Li, G. Y. (2019) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2019.2904244 · Cited by 685
Secure Control Systems: A Quantitative Risk Management Approach
(2015) · IEEE Control Systems · doi:10.1109/mcs.2014.2364709 · Cited by 316
Multiobjective Optimization in Bioinformatics and Computational Biology
Handl, J., Kell, D. B., & Knowles, J. (2007) · IEEE/ACM Transactions on Computational Biology and Bioinformatics · doi:10.1109/tcbb.2007.070203 · Cited by 308
Introduction to Multiobjective Optimization: Noninteractive Approaches
Miettinen, K. (2008) · Lecture Notes in Computer Science · doi:10.1007/978-3-540-88908-3_1 · Cited by 270
Chimera: enabling hierarchy based multi-objective optimization for self-driving laboratories
Häse, F., Roch, L. M., & Aspuru-Guzik, A. (2018) · Chemical Science · doi:10.1039/c8sc02239a · Cited by 161
Vectorial metasurface holography
Song, Q., Liu, X., Qiu, C.-W., & Genevet, P. (2022) · Applied Physics Reviews · doi:10.1063/5.0078610 · Cited by 139
AUIT – the Adaptive User Interfaces Toolkit for Designing XR Applications
Evangelista Belo, J. M., Lystbæk, M. N., Feit, A. M., Pfeuffer, K., Kán, P., Oulasvirta, A., & Grønbæk, K. (2022) · Proceedings of the 35th Annual ACM Symposium on User Interface Software and Technology · doi:10.1145/3526113.3545651 · Cited by 117
MOGOA algorithm for constrained and unconstrained multi-objective optimization problems
Tharwat, A., Houssein, E. H., Ahmed, M. M., Hassanien, A. E., & Gabel, T. (2018) · Applied Intelligence · doi:10.1007/s10489-017-1074-1 · Cited by 114
Structural damage detection-oriented multi-type sensor placement with multi-objective optimization
Lin, J.-F., Xu, Y.-L., & Law, S.-S. (2018) · Journal of Sound and Vibration · doi:10.1016/j.jsv.2018.01.047 · Cited by 83
Zeng, Z., Zhang, W., Sun, K., Wei, M., & Hong, T. (2022) · Building and Environment · doi:10.1016/j.buildenv.2021.108694 · Cited by 63
FAIR: Fair adversarial instance re-weighting
Petrović, A., Nikolić, M., Radovanović, S., Delibašić, B., & Jovanović, M. (2022) · Neurocomputing · doi:10.1016/j.neucom.2021.12.082 · Cited by 40
Augmented distributed optimization for networked systems
Xu, J. (2019) · doi:10.32657/10356/68805 · Cited by 5
Metadata
- Authors
- Marler, R. T., & Arora, J. S.
- Venue
- Structural and Multidisciplinary Optimization
- Published
- 2004-04-01
- Volume
- 26
- Issue
- 6
- Pages
- 369-395
- ISSN
- 1615-147X (ISSN-L)
- 1615-1488
- OpenAlex
- W1997188340
- Cited by
- 4,710
- References
- 0
- FWCI
- 31.97
- Type
- journal article
- Language
- en
- Open access
- closed
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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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.
