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dc.contributor.authorBaena, Daniel
dc.contributor.authorCastro Pérez, Jordi
dc.contributor.authorGonzález Alastrué, José Antonio
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Estadística i Investigació Operativa
dc.date.accessioned2015-06-16T16:38:50Z
dc.date.available2015-06-16T16:38:50Z
dc.date.created2015-06-01
dc.date.issued2015-06-01
dc.identifier.citationBaena, D; Castro, J.; Gonzalez, J. Fix-and-relax approaches for controlled tabular adjustment. "Computers & operations research", 01 Juny 2015, vol. 58, p. 41-52.
dc.identifier.issn0305-0548
dc.identifier.urihttp://hdl.handle.net/2117/28326
dc.description.abstractControlled tabular adjustment (CIA) is a relatively new protection technique for tabular data protection. CTA formulates a mixed integer linear programming problem, which is challenging for tables of moderate size. Even finding a feasible initial solution may be a challenging task for large instances. On the other hand, end users of tabular data protection techniques give priority to fast executions and are thus satisfied in practice with suboptimal solutions. This work has two goals. First, the fix-and-relax (FR) strategy is applied to obtain good feasible initial solutions to large CTA instances. FR is based on partitioning the set of binary variables into clusters to selectively explore a smaller branch-and-cut tree. Secondly, the FR solution is used as a warm start for a block coordinate descent (BCD) heuristic (approach named FR+BCD); BCD was confirmed to be a good option for large CTA instances in an earlier paper by the second and third co-authors (Comput Oper Res 2011;38:1826-35 [23]). We report extensive computational results on a set of real-world and synthetic CTA instances. FR is shown to be competitive compared to CPLEX branch-and-cut in terms of quickly finding either a feasible solution or a good upper bound. FR+BCD improved the quality of FR solutions for approximately 25% and 50% of the synthetic and real-world instances, respectively. FR or FR+BCD provided similar or better solutions in less CPU time than CPLEX for 73% of the difficult real-world instances. (C) 2015 Elsevier Ltd. All rights reserved.
dc.format.extent12 p.
dc.language.isoeng
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Spain
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Matemàtiques i estadística::Investigació operativa::Programació matemàtica
dc.subject.lcshProgramming (Mathematics)
dc.subject.otherFix-and-relax
dc.subject.otherBlock coordinate descent
dc.subject.otherMixed-integer linear programming
dc.subject.otherControlled tabular adjustment
dc.subject.otherPrimal heuristics
dc.subject.otherFeasibility pump
dc.subject.otherStatistical disclosure control
dc.subject.otherFEASIBILITY PUMP
dc.subject.otherDATA PROTECTION
dc.subject.otherSOFTWARE
dc.subject.otherTABLES
dc.subject.otherCTA
dc.titleFix-and-relax approaches for controlled tabular adjustment
dc.typeArticle
dc.subject.lemacProgramació (Matemàtica)
dc.contributor.groupUniversitat Politècnica de Catalunya. GNOM - Grup d'Optimització Numèrica i Modelització
dc.identifier.doi10.1016/j.cor.2014.11.018
dc.description.peerreviewedPeer Reviewed
dc.subject.amsClassificació AMS::90 Operations research, mathematical programming::90C Mathematical programming
dc.relation.publisherversionhttp://www.sciencedirect.com/science/article/pii/S0305054815000039
dc.rights.accessOpen Access
drac.iddocument15400224
dc.description.versionPostprint (author’s final draft)
upcommons.citation.authorBaena, D; Castro, J.; Gonzalez, J.
upcommons.citation.publishedtrue
upcommons.citation.publicationNameComputers & operations research
upcommons.citation.volume58
upcommons.citation.startingPage41
upcommons.citation.endingPage52


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Except where otherwise noted, content on this work is licensed under a Creative Commons license: Attribution-NonCommercial-NoDerivs 3.0 Spain