Parallel triangulated partitioning for black box optimization

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Title Parallel triangulated partitioning for black box optimization
Author Wu, Yong; Ozdamar, Linet; Kumar, Arun
Book Title Global Optimization
Editor Janos Pinter
Year Published 2006
Place of publication Germany
Publisher Springer
Abstract We propose a parallel triangulation based partitioning algorithm (TRIOPT) for solving low dimensional bound-constrained black box global optimization problems. Black box optimization problems are important in engineering design where restricted numbers of input-output pairs are provided as data. Optimization is carried out over sparse data in the absence of a formal mathematical relationship among inputs and outputs. In such settings, function evaluations become expensive, because system performance assessment might be conducted via simulation studies or physical experiments. Thus, the optimal solution should be found in a minimal number of function evaluations. In TRIOPT, input-output pairs are treated as samples located in the search domain and search space coverage is obtained over these samples by triangulation. This produces an initial partition of the domain. Thereafter, each simplex is assessed for re-partitioning in parallel. In this assessment, performance values at the vertices are transformed and mapped to [0,1] interval using a non-linear transformation function with dynamic parameters. Transformed values are then aggregated into a group measure
Peer Reviewed Yes
Published Yes
Alternative URI http://dx.doi.org/10.1007/0-387-30927-6_20
Chapter Number 20
Page from 487
Page to 506
ISBN 978-0-387-30408-3
Date Accessioned 2010-10-21
Date Available 2011-02-15T12:54:02Z
Language en_AU
Research Centre Institute for Integrated and Intelligent Systems
Faculty Griffith Business School
Subject Optimisation
URI http://hdl.handle.net/10072/36196
Publication Type Book Chapters
Publication Type Code b1x

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