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A Quick Practical Guide to Polyhedral Analysis in Integer Programming

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Data and Decision Sciences in Action

Part of the book series: Lecture Notes in Management and Industrial Engineering ((LNMIE))

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Abstract

Polyhedral analysis is one of the most interesting elements of integer programming and has been often overlooked. It plays an important role in finding exact solutions to an integer program. In this paper, we will discuss what polyhedral analysis is, and how some constraints for an integer programming model are “ideal” in the sense that if the model contains all of these “ideal” constraints, then the integer optimal solution can be obtained by simply solving a linear programming relaxation of the integer program. This paper serves as a quick guide for young researchers and PhD students.

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Author information

Authors and Affiliations

  1. School of Information Technology, Deakin University, Waurn Ponds, Geelong, Australia

    Vicky Mak-Hau

Authors
  1. Vicky Mak-Hau
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Corresponding author

Correspondence to Vicky Mak-Hau .

Editor information

Editors and Affiliations

  1. School of Engineering and Information Technology, University of New South Wales, Canberra, Aust Capital Terr, Australia

    Ruhul Sarker

  2. School of Engineering and Information Technology, University of New South Wales, Canberra, Aust Capital Terr, Australia

    Hussein A. Abbass

  3. Data 61, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Melbourne, Victoria, Australia

    Simon Dunstall

  4. Data 61, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Melbourne, Victoria, Australia

    Philip Kilby

  5. Strategic Capability Analysis Department, Defence Science and Technology Group, Canberra, Aust Capital Terr, Australia

    Richard Davis

  6. Department of Defence, War Research Centre, Canberra, Aust Capital Terr, Australia

    Leon Young

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Mak-Hau, V. (2018). A Quick Practical Guide to Polyhedral Analysis in Integer Programming. In: Sarker, R., Abbass, H., Dunstall, S., Kilby, P., Davis, R., Young, L. (eds) Data and Decision Sciences in Action. Lecture Notes in Management and Industrial Engineering. Springer, Cham. https://doi.org/10.1007/978-3-319-55914-8_13

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  • DOI: https://doi.org/10.1007/978-3-319-55914-8_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-55913-1

  • Online ISBN: 978-3-319-55914-8

  • eBook Packages: EngineeringEngineering (R0)

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