A systems approach to evolutionary multiobjective structural optimization and beyond
Jin Y, Sendhoff B (2009)
IEEE Computational Intelligence Magazine 4(3): 62-76.
Zeitschriftenaufsatz
| Veröffentlicht | Englisch
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Autor*in
Jin, YaochuUniBi
;
Sendhoff, Bernhard
![](https://pub.uni-bielefeld.de/images/icon_orcid.png)
Abstract / Bemerkung
Multiobjective evolutionary algorithms (MOEAs) have shown to be effective in solving a wide range of test problems. However, it is not straightforward to apply MOEAs to complex real-world problems. This paper discusses the major challenges we face in applying MOEAs to complex structural optimization, including the involvement of time-consuming and multi-disciplinary quality evaluation processes, changing environments, vagueness in formulating criteria formulation, and the involvement of multiple sub-systems. We propose that the successful tackling of all these aspects give birth to a systems approach to evolutionary design optimization characterized by considerations at four levels, namely, the system property level, temporal level, spatial level and process level. Finally, we suggest a few promising future research topics in evolutionary structural design that consist in the necessary steps towards a life-like design approach, where design principles found in biological systems such as self-organization, self-repair and scalability play a central role.
Erscheinungsjahr
2009
Zeitschriftentitel
IEEE Computational Intelligence Magazine
Band
4
Ausgabe
3
Seite(n)
62-76
ISSN
1556-603X
Page URI
https://pub.uni-bielefeld.de/record/2978620
Zitieren
Jin Y, Sendhoff B. A systems approach to evolutionary multiobjective structural optimization and beyond. IEEE Computational Intelligence Magazine. 2009;4(3):62-76.
Jin, Y., & Sendhoff, B. (2009). A systems approach to evolutionary multiobjective structural optimization and beyond. IEEE Computational Intelligence Magazine, 4(3), 62-76. https://doi.org/10.1109/MCI.2009.933094
Jin, Yaochu, and Sendhoff, Bernhard. 2009. “A systems approach to evolutionary multiobjective structural optimization and beyond”. IEEE Computational Intelligence Magazine 4 (3): 62-76.
Jin, Y., and Sendhoff, B. (2009). A systems approach to evolutionary multiobjective structural optimization and beyond. IEEE Computational Intelligence Magazine 4, 62-76.
Jin, Y., & Sendhoff, B., 2009. A systems approach to evolutionary multiobjective structural optimization and beyond. IEEE Computational Intelligence Magazine, 4(3), p 62-76.
Y. Jin and B. Sendhoff, “A systems approach to evolutionary multiobjective structural optimization and beyond”, IEEE Computational Intelligence Magazine, vol. 4, 2009, pp. 62-76.
Jin, Y., Sendhoff, B.: A systems approach to evolutionary multiobjective structural optimization and beyond. IEEE Computational Intelligence Magazine. 4, 62-76 (2009).
Jin, Yaochu, and Sendhoff, Bernhard. “A systems approach to evolutionary multiobjective structural optimization and beyond”. IEEE Computational Intelligence Magazine 4.3 (2009): 62-76.