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Interior Point Methods for Combinatorial Optimization

  • Chapter
Handbook of Combinatorial Optimization

Abstract

Interior-point methods, originally invented in the context of linear programming, have found a much broader range of applications, including discrete problems that arise in computer science and operations research as well as continuous computational problems arising in the natural sciences and engineering. This chapter describes the conceptual basis and applications of interior-point methods for discrete problems in computing.

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Authors and Affiliations

  1. Mathematical Sciences, Renssaeler Polytechnic Institute, Troy, NY, 12180, USA

    John E. Mitchell

  2. Center for Applied Optimization, ISE Department, University of Florida, Gainesville, FL, 32611, USA

    Panos M. Pardalos

  3. Information Sciences Research, AT&T Labs Research, Florham Park, NJ, 07932, USA

    Mauricio G. C. Resende

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  1. John E. Mitchell
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  2. Panos M. Pardalos
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  3. Mauricio G. C. Resende
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Editor information

Editors and Affiliations

  1. University of Minnesota, Minneapolis, USA

    Ding-Zhu Du

  2. University of Florida, Gainesville, USA

    Panos M. Pardalos

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Mitchell, J.E., Pardalos, P.M., Resende, M.G.C. (1998). Interior Point Methods for Combinatorial Optimization. In: Du, DZ., Pardalos, P.M. (eds) Handbook of Combinatorial Optimization. Springer, Boston, MA. https://doi.org/10.1007/978-1-4613-0303-9_4

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