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View all- Schütze OHernández CTalbi ESun JNaranjani YXiong F(2019)Archivers for the representation of the set of approximate solutions for MOPsJournal of Heuristics10.1007/s10732-018-9383-z25:1(71-105)Online publication date: 1-Feb-2019
Asymmetric quadratic landscape approximation model
Pages 493 - 500
Abstract
This work presents an asymmetric quadratic approximation model and an $\epsilon$-archiving algorithm. The model allows to construct, under local convexity assumptions, descriptors for local optima points in continuous functions. A descriptor can be used to extract confidence radius information. The $\epsilon$-archiving algorithm is designed to maintain and update a set of such asymmetric descriptors, spaced at some given threshold distance. An in-depth analysis is conducted on the stability and performance of the asymmetric model, comparing the results with the ones obtained by a quadratic polynomial approximation. A series of different applications are possible in areas such as dynamic and robust optimization.
Supplementary Material
In order to run all examples, simply execute 'runall.m'; asymquadapprox.m - asymmetric approximation algorithm descriptor.m - landscape descriptor that uses the same code as asymquadapprox archive.m - \epsilon-archiving algorithm archivex.m - examples of archiving examples.m - run several exmaples (creates result.mat) process.m - process results previously storred in results.mat All .mat files except result.mat are archives constructed via archivex.m.
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References
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- Asymmetric quadratic landscape approximation model
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Published: 12 July 2014
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View all- Schütze OHernández CTalbi ESun JNaranjani YXiong F(2019)Archivers for the representation of the set of approximate solutions for MOPsJournal of Heuristics10.1007/s10732-018-9383-z25:1(71-105)Online publication date: 1-Feb-2019
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