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dc.contributor.authorWu, Y.en_US
dc.contributor.authorOzdamar, L.en_US
dc.contributor.authorKumar, A.en_US
dc.date.accessioned2017-05-03T15:54:49Z
dc.date.available2017-05-03T15:54:49Z
dc.date.issued2005en_US
dc.date.modified2011-02-15T12:54:32Z
dc.identifier.issn03770427en_US
dc.identifier.doi10.1016/j.cam.2004.08.005en_AU
dc.identifier.urihttp://hdl.handle.net/10072/36209
dc.description.abstractWe propose a triangulation-based partitioning algorithm,TRIOPT, for solving low-dimensional bound-constrained black box global optimization problems. The method starts by forming a Delaunay triangulation of a given set of samples in the feasible domain, and then, it assesses the simplices (partitions) obtained for re-partitioning. Function values at the vertices of each partition are mapped into the zero one interval by a nonlinear transformation function and their aggregate entropy is calculated. Based on this entropy, partitions that hold a promise of containing the global optimum are re-partitioned according to different triangular splitting strategies, forming newpartitions. These strategies are efficient in terms of the number of new function evaluations required per new partition. A novelty in the search scheme proposed here is that once a partition narrows down to a small size, its vertices are eliminated from the available sample set. This changes global information on the best solution and triggers a re-calculation of transformed values. Hence, revised entropies change the direction of the search to new areas. The latter scheme leads to a dynamic parallel search policy which is based on an entropy cut. The tree adopts flexible breadth depending on the status of the search. In the experimental results it is demonstrated that TRIOPTs performance is compatible and often better than that of a well-known response surface methodology and two other efficient black box partitioning approaches proposed for global optimization.en_US
dc.description.peerreviewedYesen_US
dc.description.publicationstatusYesen_AU
dc.languageEnglishen_US
dc.language.isoen_AU
dc.publisherElsevier BVen_US
dc.publisher.placeNetherlandsen_US
dc.relation.ispartofstudentpublicationNen_AU
dc.relation.ispartofpagefrom35en_US
dc.relation.ispartofpageto53en_US
dc.relation.ispartofjournalJournal of Computational and Applied Mathematicsen_US
dc.relation.ispartofvolume177en_US
dc.rights.retentionYen_AU
dc.subject.fieldofresearchOptimisationen_US
dc.subject.fieldofresearchcode010303en_US
dc.titleTRIOPT: a triangulation-based partitioning algorithm for global optimizationen_US
dc.typeJournal articleen_US
dc.type.descriptionC1 - Peer Reviewed (HERDC)en_US
dc.type.codeC - Journal Articlesen_US
gro.date.issued2005
gro.hasfulltextNo Full Text


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