.png){kind=icon}
Return
A study on evolutionary multi-objective optimization for flow geometry design
.png){kind=icon}
PRE
AI
DOI：10.1007/s00466-005-0684-3.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
In this paper, we investigate three recently proposed multi-objective optimization algorithms with respect to their application to a design-optimization task in fluid dynamics. The usual approach to render optimization problems is to accumulate multiple objectives into one objective by a linear combination and optimize the resulting single-objective problem. This has severe drawbacks such that full information about design alternatives will not become visible. The multi-objective optimization algorithms NSGA-II, SPEA2 and Femo are successfully applied to a demanding shape optimizing problem in fluid dynamics. The algorithm performance will be compared on the basis of the results obtained.
Keywords:
multiobjective optimization
flow field optimization
evolutionary algorithm
Pareto set
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
3.8
Papers:
3.2K
Citations:
9.0K
Organization
No organization information available
Cited Papers
.png){kind=icon}
ShareSaveShareSaveShareSaveMultiobjective evolutionary algorithms: A comparative case study and the Strength Pareto approach
PREAI
ShareSaveShareSaveShareSave
ShareSave
View more