GRADIENT-ONLY SOLUTION STRATEGIES
Jan A. Snyman () and
Daniel N. Wilke ()
Additional contact information
Jan A. Snyman: University of Pretoria
Daniel N. Wilke: University of Pretoria
Chapter Chapter 8 in Practical Mathematical Optimization, 2018, pp 273-310 from Springer
Abstract:
Abstract Care is usually taken during the mathematical modelling and numerical computation of the scalar function $$f(\mathbf{x})$$ to ensure that it is smooth and twice continuously differentiable. As highlighted in Section 6.5, the presence of numerical noise in the objective function is sometimes an unintended consequence of the complicated numerical nature frequently associated with the computation of the output function of a multi-disciplinary design optimization model. Numerical noise can also be the consequence of a deliberate computational savings strategy employed by a design engineer. This chapter is dedicated to explore alternative formulations and solution strategies when specifically dealing with piece-wise smooth discontinuous objective functions (Wilke et al. (2013b)). In essence, this chapter elaborates and formalizes the concepts and ideas introduced and hinted to in Section 6.5, that includes the handling of noisy objective functions and the use of gradient-only optimization.
Date: 2018
References: Add references at CitEc
Citations:
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:spochp:978-3-319-77586-9_8
Ordering information: This item can be ordered from
http://www.springer.com/9783319775869
DOI: 10.1007/978-3-319-77586-9_8
Access Statistics for this chapter
More chapters in Springer Optimization and Its Applications from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().