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

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dc.contributor.authorAbramson, Mark A.en_US
dc.contributor.authorAsaki, Thomas J.en_US
dc.contributor.authorDennis, J.E. Jr.en_US
dc.contributor.authorMagallanez, Raymonden_US
dc.contributor.authorSottile, Matthew J.en_US
dc.date.accessioned2018-06-19T17:13:02Zen_US
dc.date.available2018-06-19T17:13:02Zen_US
dc.date.issued2008-06en_US
dc.date.noteJune 2008 (Revised April 2011)en_US
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.en_US
dc.format.extent20 ppen_US
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>.en_US
dc.identifier.urihttps://hdl.handle.net/1911/102088en_US
dc.language.isoengen_US
dc.titleAn Efficient Class of Direct Search Surrogate Methods for Solving Expensive Optimization Problems with CPU-Time-Related Functionsen_US
dc.typeTechnical reporten_US
dc.type.dcmiTexten_US
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