An Efficient Class of Direct Search Surrogate Methods for Solving Expensive Optimization Problems with CPU-Time-Related Functions

Simple item page
dc.contributor.authorAbramson, Mark A.
dc.contributor.authorAsaki, Thomas J.
dc.contributor.authorDennis, J.E. Jr.
dc.contributor.authorMagallanez, Raymond
dc.contributor.authorSottile, Matthew J.
dc.date.accessioned2018-06-19T17:13:02Z
dc.date.available2018-06-19T17:13:02Z
dc.date.issued2008-06
dc.date.noteJune 2008 (Revised April 2011)
dc.description.abstractIn this paper, we characterize a new class of computationally expensive optimization problems and introduce an approach for solving them. In this class of problems, objective function values may be directly related to the computational time required to obtain them, so that, as the optimal solution is approached, the computational time required to evaluate the objective is significantly less than at points farther away from the solution. This is motivated by an application in which each objective function evaluation requires both a numerical fluid dynamics simulation and an image registration process, and the goal is to find the parameter values of a predetermined reference image by comparing the flow dynamics from the numerical simulation and the reference image through the image comparison process. In designing an approach to numerically solve the more general class of problems in an efficient way, we make use of surrogates based on CPU times of previously evaluated points, rather than their function values, all within the search step framework of mesh adaptive direct search algorithms. Because of the expected positive correlation between function values and their CPU times, a time cutoff parameter is added to the objective function evaluation to allow its termination during the comparison process if the computational time exceeds a specified threshold. The approach was tested using the NOMADm and DACE MATLAB software packages, and results are presented.
dc.format.extent20 pp
dc.identifier.citationAbramson, Mark A., Asaki, Thomas J., Dennis, J.E. Jr., et al.. "An Efficient Class of Direct Search Surrogate Methods for Solving Expensive Optimization Problems with CPU-Time-Related Functions." (2008) <a href="https://hdl.handle.net/1911/102088">https://hdl.handle.net/1911/102088</a>.
dc.identifier.urihttps://hdl.handle.net/1911/102088
dc.language.isoeng
dc.titleAn Efficient Class of Direct Search Surrogate Methods for Solving Expensive Optimization Problems with CPU-Time-Related Functions
dc.typeTechnical report
dc.type.dcmiText
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
TR08-06.pdf
Size:
365.38 KB
Format:
Adobe Portable Document Format
Description:
Download
Collections
CAAM Technical Reports