## A modified adaptive random-search algorithm for the design of helical gears has been developed. The proposed methodology allows for the implementation of nonlinear design functions and constraints without the need for linearization. In addition, the technique has the capability of starting from e
Optimal design with the aid of randomization methods
โ Scribed by C. M. Kalker-Kalkman
- Publisher
- Springer
- Year
- 1991
- Tongue
- English
- Weight
- 869 KB
- Volume
- 7
- Category
- Article
- ISSN
- 0177-0667
No coin nor oath required. For personal study only.
๐ SIMILAR VOLUMES
Optimum engineering design problems are usually formulated as non-convex optimization problems of continuous variables. Because of the absence of convexity structure, they can have multiple minima, and global optimization becomes difficult. Traditional methods of optimization, such as penalty method
Uncertainties in applied loads are introduced into the theory of optimization by use of ellipsoidal convex models. Mathematical derivations for quantifying uncertainty with the convex model are presented and are incorporated into an optimization computer algorithm. The algorithm is used in two desig