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Optimization of large-scale structured problems. Application to data confidentiality

Total activity: 24
Type of activity
Competitive project
Funding entity
Funding entity code
35.100,00 €
Start date
End date
confidencialidad de datos, métodos de punto interior, optimización computacional, optimización de gran escala, optimización entera, optimización matemática, problemas estructurados
Data confidentiality is a relatively recent field of application of mathematical programming, and in previous
years provided real-world, large and challenging optimization problems (both continuous and discrete).
The research group is internationally recognized by the application of optimization methods to tabular data
protection. International conferences such as EURO-XXV (Lithuania, July 2012) include a stream
Statistical Data Confidentiality, coorganized by the research group.
The research group recently suggested and worked on a perturbative approach named “controlled tabular
adjustment” (CTA). This method formulates a linear or quadratic optimization problem (depending on the
distance used), with binary variables, and often structured depending on the format of the tables. This
approach has been implemented by the group for Eurostat using commercial state-of-the-art optimization
solvers. Heuristic approximations developed by the group provided suboptimal solutions within a
reasonable time for large mixed integer linear problems (of one million continuous and 50000 binary
variables); some of the best commercial solvers could not even provide a feasible solution with these
instances (some solvers, such as CPLEX, asked for some of these instances for benchmarking). Decent
results have also been obtained solving CTA with Euclidean distances, which results in a mixed integer
quadratic optimization problem.
Up to now, perturbative data protection methods were applied to a predefined set of “static” tables. This
allowed the (suboptimal) solution of the mixed integer problem within a time limit. In the recently started
project “DwB. Data without Boundaries” (INFRA-2010-262608 VII Mark Program of the EU), we being one
of the partners, a new paradigm is considered: the protection of tables obtained through on-line servers.
Protection has to be performed in real-time in this new context. This means that binary variables have to
be a priori fixed, and a fast solution to the resulting convex continuous optimization problem is required
(guaranteeing feasibility). Interior-point methods are a good choice in this case because (i) they showed to
be more efficient than simplex-like methods for these problems; (ii) the primal-dual path following
algorithm, the most efficient approach in practice, may provide a fast suboptimal feasible solution with
information of the optimality gap. Moreover, iterative methods for the Newton’s equation at each interiorpoint
iteration can be used for a fast solution of very large instances, both for problems with and without
structure. Good results have been obtained for three-dimensional tables solving problems of up to 40
million variables in reasonable times. These results should be extended to more general tables.
The main objectives of the project are thus: 1) Development of interior-point methods for large scale
problems, with and without structure. 2) Development and application of iterative methods
(preconditioners, regularizations) in interior-point methods. 3) Application of interior-point methods to the
continuous CTA problem in on-line servers. 4) Development of approaches for the (likely suboptimal)
solution of large scale mixed integer linear problems. 5) Application to the mixed CTA problem in static
Adm. Estat
Plan Nacional de Investigación Científica, Desarrollo e Innovación Tecnológica 2008-2011
Call year
Funcding program
Funding subprogram
Funding call
Proyectos de investigación y acciones complementarias-MTM
Grant institution
Gobierno De España. Ministerio De Economía Y Competitividad, Mineco


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