Skip to Main Content

Engineering Optimization: Applications, Methods, and Analysis

By
R. Russell Rhinehart
R. Russell Rhinehart
Search for other works by this author on:
ISBN:
9781118936337
No. of Pages:
770
Publisher:
ASME Press
Publication date:
2018

This chapter presents two search algorithms that use second-order models of the surface: successive quadratic (SQ) and Newton–Raphson (NR). They presume more about the surface than the gradient-based optimizers. Consequently these are faster when the surface is compatible with the algorithm concepts, which include continuum deterministic surfaces, no flat spots, and an initial trial solution in the vicinity of the optimum. These optimization approaches often are accepted as the premier optimization methods, and they are components in next-level gradient-based optimizers. So, they need to be presented, even though I find that they are wholly inappropriate for many applications, which have features that are inconsistent with the concepts on which these algorithms are predicated.

This content is only available via PDF.
Close Modal
This Feature Is Available To Subscribers Only

Sign In or Create an Account

Close Modal
Close Modal