The DOI matches its Crossref record; 84 of the 84 references it cites were found in a registry or an index.
Data-Driven Evolutionary Optimization: An Overview and Case Studies
Open accessAbstract
Most evolutionary optimization algorithms assume that the evaluation of the objective and constraint functions is straightforward. In solving many real-world optimization problems, however, such objective functions may not exist. Instead, computationally expensive numerical simulations or costly physical experiments must be performed for fitness evaluations. In more extreme cases, only historical data are available for performing optimization and no new data can be generated during optimization. Solving evolutionary optimization problems driven by data collected in simulations, physical experiments, production processes, or daily life are termed data-driven evolutionary optimization. In this paper, we provide a taxonomy of different data driven evolutionary optimization problems, discuss main challenges in data-driven evolutionary optimization with respect to the nature and amount of data, and the availability of new data during optimization. Real-world application examples are given to illustrate different model management strategies for different categories of data-driven optimization problems.
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Cites
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Cited by
Hua, Y., Liu, Q., Hao, K., & Jin, Y. (2021) · IEEE/CAA Journal of Automatica Sinica · doi:10.1109/jas.2021.1003817 · Cited by 346
Self-citationMinimalistic Attacks: How Little It Takes to Fool Deep Reinforcement Learning Policies
Qu, X., Sun, Z., Ong, Y.-S., Gupta, A., & Wei, P. (2021) · IEEE Transactions on Cognitive and Developmental Systems · doi:10.1109/tcds.2020.2974509 · Cited by 40
Song, Z., Wang, H., & Jin, Y. (2023) · IEEE Transactions on Systems Man and Cybernetics Systems · doi:10.1109/tsmc.2023.3281822 · Cited by 38
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Metadata
- Authors
- Jin, Y., Wang, H., Chugh, T., Guo, D., & Miettinen, K.
- Venue
- IEEE Transactions on Evolutionary Computation
- Published
- 2019-06
- Volume
- 23
- Issue
- 3
- Pages
- 442-458
- ISSN
- 1089-778X (ISSN-L)
- 1941-0026
- OpenAlex
- W2891186800
- Cited by
- 686
- References
- 84
- FWCI
- 23.76
- Type
- journal article
- Language
- en
- Open access
- green
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