Selective Search for Global Optimization of Zero or Small Residual Least-Squares Problems: A Numerical Study

Simple item page
dc.contributor.authorVelazquez, Leticia
dc.contributor.authorPhillips, George
dc.contributor.authorTapia, Richard
dc.contributor.authorZhang,Yin
dc.date.accessioned2018-06-18T17:47:34Z
dc.date.available2018-06-18T17:47:34Z
dc.date.issued1999-09
dc.date.noteSeptember 1999
dc.description.abstractIn this paper, we consider searching for global minima of zero or small residual, nonlinear least-squares problems. We propose a selective search approach based on the concept of selective minimization recently introduced in Zhang et al[14]. To test the viability of the proposed approach, we construct a simple implementation using a Levenberg-Marquardt type method combined with a multi-start scheme, and compare it with several existing global optimization techniques. Numerical experiments were performed on zero residual nonlinear least-squares problem chosen from structural biology applications as well as from the literature. On the problems of larger sizes, the performance of the new approach compared favorably with the other tested methods, indicating that the new approach is promising for the intended class of problems.
dc.format.extent17 pp
dc.identifier.citationVelazquez, Leticia, Phillips, George, Tapia, Richard, et al.. "Selective Search for Global Optimization of Zero or Small Residual Least-Squares Problems: A Numerical Study." (1999) <a href="https://hdl.handle.net/1911/101925">https://hdl.handle.net/1911/101925</a>.
dc.identifier.digitalTR99-20
dc.identifier.urihttps://hdl.handle.net/1911/101925
dc.language.isoeng
dc.titleSelective Search for Global Optimization of Zero or Small Residual Least-Squares Problems: A Numerical Study
dc.typeTechnical report
dc.type.dcmiText
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
TR99-20.pdf
Size:
222.55 KB
Format:
Adobe Portable Document Format
Download
Collections
CAAM Technical Reports