Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/93320
DC Field | Value | Language |
---|---|---|
dc.contributor | Department of Applied Mathematics | en_US |
dc.creator | Wang, J | en_US |
dc.creator | Hu, Y | en_US |
dc.creator | Yu, CKW | en_US |
dc.creator | Li, C | en_US |
dc.creator | Yang, X | en_US |
dc.date.accessioned | 2022-06-15T03:42:43Z | - |
dc.date.available | 2022-06-15T03:42:43Z | - |
dc.identifier.issn | 1052-6234 | en_US |
dc.identifier.uri | http://hdl.handle.net/10397/93320 | - |
dc.language.iso | en | en_US |
dc.publisher | Society for Industrial and Applied Mathematics | en_US |
dc.rights | © 2019 Society for Industrial and Applied Mathematics | en_US |
dc.rights | The following publication Wang, J., Hu, Y., Wai Yu, C. K., Li, C., & Yang, X. (2019). Extended Newton methods for multiobjective optimization: majorizing function technique and convergence analysis. SIAM Journal on Optimization, 29(3), 2388-2421 is available at https://doi.org/10.1137/18M1191737 | en_US |
dc.subject | Convergence criteria | en_US |
dc.subject | L-average Lipschitz condition | en_US |
dc.subject | Multiobjective optimization | en_US |
dc.subject | Newton method | en_US |
dc.subject | Pareto optimum | en_US |
dc.title | Extended newton methods for multiobjective optimization : majorizing function technique and convergence analysis | en_US |
dc.type | Journal/Magazine Article | en_US |
dc.identifier.spage | 2388 | en_US |
dc.identifier.epage | 2421 | en_US |
dc.identifier.volume | 29 | en_US |
dc.identifier.issue | 3 | en_US |
dc.identifier.doi | 10.1137/18M1191737 | en_US |
dcterms.abstract | We consider the extended Newton method for approaching a Pareto optimum of a multiobjective optimization problem, establish quadratic convergence criteria, and estimate a radius of convergence ball under the assumption that the Hessians of objective functions satisfy an L-average Lipschitz condition. These convergence theorems significantly improve the corresponding ones in [J. Fliege, L. M. G. Drummond, and B. F. Svaiter, SIAM J. Optim., 20 (2009), pp. 602-626]. As applications of the obtained results, convergence theorems under the classical Lipschitz condition or the γ-condition are presented for multiobjective optimization, and the global quadratic convergence results of the extended Newton method with Armijo/Goldstein/Wolfe line-search schemes are also provided. | en_US |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | SIAM journal on optimization, 2019, v. 29, no. 3, p. 2388-2421 | en_US |
dcterms.isPartOf | SIAM journal on optimization | en_US |
dcterms.issued | 2019 | - |
dc.identifier.scopus | 2-s2.0-85095960746 | - |
dc.identifier.eissn | 1095-7189 | en_US |
dc.description.validate | 202206 bcfc | en_US |
dc.description.oa | Version of Record | en_US |
dc.identifier.FolderNumber | AMA-0261 | - |
dc.description.fundingSource | RGC | en_US |
dc.description.pubStatus | Published | en_US |
dc.identifier.OPUS | 23263637 | - |
Appears in Collections: | Journal/Magazine Article |
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18m1191737.pdf | 712.38 kB | Adobe PDF | View/Open |
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