Accelerating evolutionary algorithms with Gaussian process fitness function models
dc.contributor.author | Buche, Dirk | |
dc.contributor.author | Schraudolph, Nicol | |
dc.contributor.author | Koumoutsakos, Petros | |
dc.date.accessioned | 2015-12-13T22:59:33Z | |
dc.date.available | 2015-12-13T22:59:33Z | |
dc.date.issued | 2005 | |
dc.date.updated | 2015-12-12T07:29:20Z | |
dc.description.abstract | We present an overview of evolutionary algorithms that use empirical models of the fitness function to accelerate convergence, distinguishing between evolution control and the surrogate approach. We describe the Gaussian process model and propose using it as an inexpensive fitness function surrogate. Implementation issues such as efficient and numerically stable computation, exploration versus exploitation, local modeling, multiple objectives and constraints, and failed evaluations are addressed. Our resulting Gaussian process optimization procedure clearly outperforms other evolutionary strategies on standard test functions as well as on a real-world problem: The optimization of stationary gas turbine compressor profiles. | |
dc.identifier.issn | 1094-6977 | |
dc.identifier.uri | http://hdl.handle.net/1885/83863 | |
dc.publisher | Institute of Electrical and Electronics Engineers (IEEE Inc) | |
dc.source | IEEE Transactions on Systems, Man and Cybernetics. Part C: Applications and Reviews | |
dc.source.uri | http://ieeexplore.ieee.org/xpl/tocresult.jsp?isYear=2005&isnumber=30750&Submit32=Go+To+Issues | |
dc.subject | Keywords: Compressors; Computation theory; Control system synthesis; Convergence of numerical methods; Functions; Gas turbines; Mathematical models; Optimization; Evolution control; Fitness function modeling; Gas turbine compressor design; Gaussian process; Surroga Evolution control; Evolutionary algorithms (EAs); Fitness function modeling; Gas turbine compressor design; Gaussian process; Surrogate approach | |
dc.title | Accelerating evolutionary algorithms with Gaussian process fitness function models | |
dc.type | Journal article | |
local.bibliographicCitation.issue | 2 | |
local.bibliographicCitation.lastpage | 194 | |
local.bibliographicCitation.startpage | 183 | |
local.contributor.affiliation | Buche, Dirk, Swiss Federal Institute of Technology (ETH) | |
local.contributor.affiliation | Schraudolph, Nicol, College of Engineering and Computer Science, ANU | |
local.contributor.affiliation | Koumoutsakos, Petros, Swiss Federal Institute of Technology (ETH) | |
local.contributor.authoremail | repository.admin@anu.edu.au | |
local.contributor.authoruid | Schraudolph, Nicol, a205905 | |
local.description.notes | Imported from ARIES | |
local.description.refereed | Yes | |
local.identifier.absfor | 080109 - Pattern Recognition and Data Mining | |
local.identifier.ariespublication | MigratedxPub12142 | |
local.identifier.citationvolume | C35 | |
local.identifier.scopusID | 2-s2.0-18544390529 | |
local.identifier.uidSubmittedBy | Migrated | |
local.type.status | Published Version |