Data Correcting Approach for the Maximization of Submodular Functions

  • Boris Goldengorin
  • Panos M. Pardalos
Part of the SpringerBriefs in Optimization book series (BRIEFSOPTI)


The data correcting (DC) algorithm is a recursive Branch-and-Bound (BnB) type algorithm, in which the data of a given problem instance are “heuristically corrected” at each branching in such a way that the new instance will be as close as possible to polynomially solvable and the result satisfies a prescribed accuracy (the difference between optimal and current solution). The main idea of the data correcting approach for an arbitrary function z defined on a set S can be described as follows (see e.g., [66]).


Computational Experiment Data Correct Edge Density Hasse Diagram Submodular Function 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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© Boris Goldengorin, Panos M. Pardalos 2012

Authors and Affiliations

  • Boris Goldengorin
    • 1
    • 2
  • Panos M. Pardalos
    • 3
    • 4
  1. 1.Laboratory of Algorithms and Technologies for Networks Analysis (LATNA) and Department of Higher MathematicsNational Research University Higher School of EconomicsMoscowRussia
  2. 2.Operations DepartmentUniversity of GroningenGroningenThe Netherlands
  3. 3.Center for Applied Optimization Department of Industrial and Systems EngineeringUniversity of FloridaGainesvilleUSA
  4. 4.Laboratory of Algorithms and Technologies for Networks Analysis (LATNA)National Research University Higher School of EconomicsMoscowRussia

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