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Book cover Data Correcting Approaches in Combinatorial Optimization

Part of the book series: SpringerBriefs in Optimization ((BRIEFSOPTI))

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Abstract

In this book we study a class of algorithms for solving NP-hard problems called data correcting algorithms. A data correcting (DC) algorithm is a branch-and-bound type algorithm, in which the data of a given problem is “heuristically corrected” at the various stages in such a way that the new instance will be polynomially solvable and its optimal solution is within a prespecified deviation (called prescribed accuracy) from the optimal solution to the original problem.

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Authors and Affiliations

  1. Laboratory of Algorithms and Technologies for Networks Analysis (LATNA) and Department of Higher Mathematics, National Research University Higher School of Economics, Moscow, Russia

    Boris Goldengorin

  2. Operations Department, University of Groningen, Groningen, The Netherlands

    Boris Goldengorin

  3. Center for Applied Optimization Department of Industrial and Systems Engineering, University of Florida, 401 Weil Hall, Gainesville, FL, USA

    Panos M. Pardalos

  4. Laboratory of Algorithms and Technologies for Networks Analysis (LATNA), National Research University Higher School of Economics, Moscow, Russia

    Panos M. Pardalos

Authors
  1. Boris Goldengorin
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  2. Panos M. Pardalos
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© 2012 Boris Goldengorin, Panos M. Pardalos

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Goldengorin, B., Pardalos, P.M. (2012). Summary. In: Data Correcting Approaches in Combinatorial Optimization. SpringerBriefs in Optimization. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-5286-7_5

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