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50 Years of Integer Programming 1958-2008 pp 561–618Cite as

Nonlinear Integer Programming

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Abstract

Research efforts of the past fifty years have led to a development of linear integer programming as a mature discipline of mathematical optimization. Such a level of maturity has not been reached when one considers nonlinear systems subject to integrality requirements for the variables. This chapter is dedicated to this topic. The primary goal is a study of a simple version of general nonlinear integer problems, where all constraints are still linear. Our focus is on the computational complexity of the problem, which varies significantly with the type of nonlinear objective function in combination with the underlying combinatorial structure. Numerous boundary cases of complexity emerge, which sometimes surprisingly lead even to polynomial time algorithms.We also cover recent successful approaches for more general classes of problems. Though no positive theoretical efficiency results are available, nor are they likely to ever be available, these seem to be the currently most successful and interesting approaches for solving practical problems. It is our belief that the study of algorithms motivated by theoretical considerations and those motivated by our desire to solve practical instances should and do inform one another. So it is with this viewpoint that we present the subject, and it is in this direction that we hope to spark further research.

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Authors and Affiliations

  1. FMA/IMO, Otto-von-Guericke-Universität Magdeburg, Magdeburg, Germany

    Raymond Hemmecke & Robert Weismantel

  2. Department of Mathematics, University of California, Davis, USA

    Matthias Köppe

  3. IBM T.J. Watson Research Center, Yorktown Heights, New York, USA

    Jon Lee

Authors
  1. Raymond Hemmecke
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  2. Matthias Köppe
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  3. Jon Lee
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  4. Robert Weismantel
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Correspondence to Raymond Hemmecke .

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Editors and Affiliations

  1. Inst. Informatik, Universität Köln, Pohligstr. 1, Köln, 50969, Germany

    Michael Jünger

  2. Fac. Sciences de Base (FSB), Ecole Polytechnique Fédérale de Lausanne, Lausanne, 1015, Switzerland

    Thomas M. Liebling

  3. Ensimag, Institut Polytechnique de Grenoble, avenue Félix Viallet 46, Grenoble CX 1, 38031, France

    Denis Naddef

  4. School of Industrial &, Georgia Institute of Technology, Ferst Drive NW., 765, Atlanta, 30332-0205, USA

    George L. Nemhauser

  5. IBM Corporation, Route 100 294, Somers, 10589, USA

    William R. Pulleyblank

  6. Inst. Informatik, Universität Heidelberg, Im Neuenheimer Feld 326, Heidelberg, 69120, Germany

    Gerhard Reinelt

  7. ed Informatica, CNR - Ist. Analisi dei Sistemi, Viale Manzoni 30, Roma, 00185, Italy

    Giovanni Rinaldi

  8. Center for Operations Reserach &, Université Catholique de Louvain, voie du Roman Pays 34, Leuven, 1348, Belgium

    Laurence A. Wolsey

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Hemmecke, R., Köppe, M., Lee, J., Weismantel, R. (2010). Nonlinear Integer Programming. In: Jünger, M., et al. 50 Years of Integer Programming 1958-2008. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-68279-0_15

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