Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/110065
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dc.contributorDepartment of Applied Mathematics-
dc.creatorRagonneau, TM-
dc.creatorZhang, Z-
dc.date.accessioned2024-11-20T07:31:43Z-
dc.date.available2024-11-20T07:31:43Z-
dc.identifier.issn1867-2949-
dc.identifier.urihttp://hdl.handle.net/10397/110065-
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.rights© The Author(s) 2024en_US
dc.rightsThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.en_US
dc.rightsThe following publication Ragonneau, T.M., Zhang, Z. PDFO: a cross-platform package for Powell’s derivative-free optimization solvers. Math. Prog. Comp. 16, 535–559 (2024) is available at https://doi.org/10.1007/s12532-024-00257-9.en_US
dc.subjectBOBYQAen_US
dc.subjectCOBYLAen_US
dc.subjectDerivative-free optimizationen_US
dc.subjectLINCOAen_US
dc.subjectNEWUOAen_US
dc.subjectUOBYQAen_US
dc.titlePDFO : a cross-platform package for Powell’s derivative-free optimization solversen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage535-
dc.identifier.epage559-
dc.identifier.volume16-
dc.identifier.issue4-
dc.identifier.doi10.1007/s12532-024-00257-9-
dcterms.abstractThe late Professor M. J. D. Powell devised five trust-region methods for derivative-free optimization, namely COBYLA, UOBYQA, NEWUOA, BOBYQA, and LINCOA. He carefully implemented them into publicly available solvers, renowned for their robustness and efficiency. However, the solvers were implemented in Fortran 77 and hence may not be easily accessible to some users. We introduce the PDFO package, which provides user-friendly Python and MATLAB interfaces to Powell’s code. With PDFO, users of such languages can call Powell’s Fortran solvers easily without dealing with the Fortran code. Moreover, PDFO includes bug fixes and improvements, which are particularly important for handling problems that suffer from ill-conditioning or failures of function evaluations. In addition to the PDFO package, we provide an overview of Powell’s methods, sketching them from a uniform perspective, summarizing their main features, and highlighting the similarities and interconnections among them. We also present experiments on PDFO to demonstrate its stability under noise, tolerance of failures in function evaluations, and potential to solve certain hyperparameter optimization problems.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationMathematical programming computation, Dec. 2024, v. 16, no. 4, p. 535-559-
dcterms.isPartOfMathematical programming computation-
dcterms.issued2024-12-
dc.identifier.scopus2-s2.0-85206609515-
dc.identifier.eissn1867-2957-
dc.description.validate202411 bcch-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_TAen_US
dc.description.fundingSourceRGCen_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextThe Hong Kong Polytechnic University; CASCroucher Funding Schemeen_US
dc.description.pubStatusPublisheden_US
dc.description.TASpringer Nature (2024)en_US
dc.description.oaCategoryTAen_US
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