A fix-and-relax heuristic for controlled tabular adjustment
Controlled tabular adjustment (CTA) is an emerging protect ion technique for tabular data pro- tection. CTA formulates a mixed integer linear programming problem, which is tough for tables of moderate size. Finding a feasible initial solution may ev en be a challenging task for large instances. On t...
| Autores: | , |
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| Tipo de recurso: | informe técnico |
| Fecha de publicación: | 2013 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/21030 |
| Acceso en línea: | https://hdl.handle.net/2117/21030 |
| Access Level: | acceso abierto |
| Palabra clave: | Programming (Mathematics) Programació (Matemàtica) 90C Programació matemàtica Àrees temàtiques de la UPC::Matemàtiques i estadística::Investigació operativa::Programació matemàtica |
| Sumario: | Controlled tabular adjustment (CTA) is an emerging protect ion technique for tabular data pro- tection. CTA formulates a mixed integer linear programming problem, which is tough for tables of moderate size. Finding a feasible initial solution may ev en be a challenging task for large instances. On the other hand, end users of tabular data prote ction techniques give priority to fast executions and are thus satisfied in practice with suboptima l solutions. In this work the fix-and- relax strategy is applied to large CTA instances. Fix-and-r elax is based on partitioning the set of binary variables into clusters to selectively explore a sma ller branch-and-cut tree. We report ex- tensive computational results on a set of real and random CTA instances. Fix-and-relax is shown to be competitive compared to plain CPLEX branch-and-cut in terms of quickly finding either a feasible solution or a good upper bound in di ffi cult instances. |
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