Offline data-driven evolutionary optimization based on tri-training

Huang P, Wang H, Jin Y (2021)
Swarm and Evolutionary Computation 60: 100800.

Zeitschriftenaufsatz | Veröffentlicht | Englisch
 
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Autor*in
Huang, Pengfei; Wang, Handing; Jin, YaochuUniBi
Abstract / Bemerkung
In offline data-driven evolutionary optimization, no real fitness evaluations is allowed during the optimization, making it extremely challenging to build high-quality surrogates on limited amount of data. This is especially true for large-scale optimization problems where typically a large amount of data is needed for constructing reliable surrogate models. To overcome the data deficiency, semi-supervised learning is introduced to the offline data-driven evolutionary optimization process, where tri-training, a co-training variant, is used to update surrogate models. In the proposed algorithm, a tri-training algorithm selects candidate solutions with high-confidence fitness prediction to enrich the training data for surrogate models. The results on benchmark problems show that the proposed algorithm, compared with three most recent offline data-driven optimization algorithms, is competitive on the problems of up to 500 decision variables.
Erscheinungsjahr
2021
Zeitschriftentitel
Swarm and Evolutionary Computation
Band
60
Art.-Nr.
100800
ISSN
2210-6502
Page URI
https://pub.uni-bielefeld.de/record/2978389

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Huang P, Wang H, Jin Y. Offline data-driven evolutionary optimization based on tri-training. Swarm and Evolutionary Computation. 2021;60: 100800.
Huang, P., Wang, H., & Jin, Y. (2021). Offline data-driven evolutionary optimization based on tri-training. Swarm and Evolutionary Computation, 60, 100800. https://doi.org/10.1016/j.swevo.2020.100800
Huang, Pengfei, Wang, Handing, and Jin, Yaochu. 2021. “Offline data-driven evolutionary optimization based on tri-training”. Swarm and Evolutionary Computation 60: 100800.
Huang, P., Wang, H., and Jin, Y. (2021). Offline data-driven evolutionary optimization based on tri-training. Swarm and Evolutionary Computation 60:100800.
Huang, P., Wang, H., & Jin, Y., 2021. Offline data-driven evolutionary optimization based on tri-training. Swarm and Evolutionary Computation, 60: 100800.
P. Huang, H. Wang, and Y. Jin, “Offline data-driven evolutionary optimization based on tri-training”, Swarm and Evolutionary Computation, vol. 60, 2021, : 100800.
Huang, P., Wang, H., Jin, Y.: Offline data-driven evolutionary optimization based on tri-training. Swarm and Evolutionary Computation. 60, : 100800 (2021).
Huang, Pengfei, Wang, Handing, and Jin, Yaochu. “Offline data-driven evolutionary optimization based on tri-training”. Swarm and Evolutionary Computation 60 (2021): 100800.
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