Answers are grounded in this paper and cite their sources.
The flutter/divergence speed of a simple rectangular composite wing is maximized through the use of different ply orientations. Four different biologically inspired optimization algorithms (binary genetic algorithm, continuous genetic algorithm, particle swarm optimization, and ant colony optimization) and a simple meta-modeling approach are employed statistically on the same problem set. In terms of the best flutter speed, it was found that similar results were obtained using all of the methods, although the continuous methods gave better answers than the discrete methods. When the results were considered in terms of the statistical variation between different solutions, ant colony optimization gave estimates with much less scatter.
No takes yet. Share an insight, caveat, or question.
Manan et al. (2009) studied this question.
Synapse has enriched 10 related papers. Consider them for comparative context: