Full Content is available to subscribers

Subscribe/Learn More  >

Improving Multi-Objective Genetic Algorithm Efficiency for Computational Expensive Problems Adopting Online Variable-Fidelity Metamodel

[+] Author Affiliations
Leshi Shu, Ping Jiang, Qi Zhou, Xiangzheng Meng, Yahui Zhang

Huazhong University of Science & Technology, Wuhan, China

Paper No. DETC2018-86308, pp. V02BT03A044; 9 pages
  • ASME 2018 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
  • Volume 2B: 44th Design Automation Conference
  • Quebec City, Quebec, Canada, August 26–29, 2018
  • Conference Sponsors: Design Engineering Division, Computers and Information in Engineering Division
  • ISBN: 978-0-7918-5176-0
  • Copyright © 2018 by ASME


Multi-objective genetic algorithms (MOGAs) are effective ways for obtaining Pareto solutions of multi-objective optimization problems. However, the high computational cost of MOGAs limits their applications to practical engineering optimization problems involving computational expensive simulations. To address this issue, a variable-fidelity metamodel (VFM) assisted MOGA approach is proposed, in which VFM is embedded in the computation process of MOGA to replace expensive simulation models. The VFM is updated in the optimization process considering the cost of simulation models with different fidelity and the effects of the VFM uncertainty. A numerical example and an engineering case are used to demonstrate the applicability and efficiency of the proposed approach. The results show that the proposed approach can obtain Pareto solutions with high quality and it outperforms the other three existing approaches in terms of computational efficiency.

Copyright © 2018 by ASME



Interactive Graphics


Country-Specific Mortality and Growth Failure in Infancy and Yound Children and Association With Material Stature

Use interactive graphics and maps to view and sort country-specific infant and early dhildhood mortality and growth failure data and their association with maternal

Citing articles are presented as examples only. In non-demo SCM6 implementation, integration with CrossRef’s "Cited By" API will populate this tab (http://www.crossref.org/citedby.html).

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In