Reference : Asymmetric quadratic landscape approximation model
Scientific congresses, symposiums and conference proceedings : Paper published in a journal
Engineering, computing & technology : Computer science
Asymmetric quadratic landscape approximation model
Tantar, Alexandru-Adrian mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Tantar, Emilia mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Schütze, O. [Computer Science Department, CINVESTAV-IPN, Av. IPN 2508, Col. San Pedro Zacatenco, Mexico City, Mexico]
GECCO 2014 - Proceedings of the 2014 Genetic and Evolutionary Computation Conference
Association for Computing Machinery
16th Genetic and Evolutionary Computation Conference, GECCO 2014
12 July 2014 through 16 July 2014
Vancouver, BC
[en] Optimization ; Polynomial approximation ; Asymmetric models ; Continuous functions ; In-depth analysis ; Landscape approximation ; Local convexities ; Quadratic approximation ; Robust optimization ; Threshold distances ; Approximation algorithms
[en] This work presents an asymmetric quadratic approximation model and an ε-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 ε-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. © 2014 ACM.

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