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Optimal Coverage in Automotive Configuration

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Mathematical Aspects of Computer and Information Sciences (MACIS 2015)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9582))

Abstract

It is a problem in automotive configuration to determine the minimum number of test vehicles which are needed for testing a given set of equipment options. This problem is related to the minimum set cover problem, but with the additional restriction that we can not enumerate all vehicle variants since in practice their number is far too large for each model type. In this work we illustrate different use cases of minimum set cover computations in the context of automotive configuration. We give formal problem definitions and we develop different approximate (greedy) and exact algorithms. Based on benchmarks of a German premium car manufacturer we evaluate our different approaches to compare their time and quality and to determine tradeoffs.

R. Walter and T. Kübart—Contributed equally to this work.

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Author information

Authors and Affiliations

  1. Symbolic Computation Group, WSI Informatics, Eberhard-Karls-Universität, Tübingen, Germany

    Rouven Walter, Thore Kübart & Wolfgang Küchlin

  2. Steinbeis Technology Transfer Centre STZ OIT, Tübingen, Germany

    Rouven Walter, Thore Kübart & Wolfgang Küchlin

Authors
  1. Rouven Walter
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  2. Thore Kübart
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  3. Wolfgang Küchlin
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Corresponding author

Correspondence to Rouven Walter .

Editor information

Editors and Affiliations

  1. Wilfrid Laurier University, Waterloo, Ontario, Canada

    Ilias S. Kotsireas

  2. Hamburg University of Technology, Hamburg, Germany

    Siegfried M. Rump

  3. New York University, New York, New York, USA

    Chee K. Yap

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Walter, R., Kübart, T., Küchlin, W. (2016). Optimal Coverage in Automotive Configuration. In: Kotsireas, I., Rump, S., Yap, C. (eds) Mathematical Aspects of Computer and Information Sciences. MACIS 2015. Lecture Notes in Computer Science(), vol 9582. Springer, Cham. https://doi.org/10.1007/978-3-319-32859-1_52

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  • DOI: https://doi.org/10.1007/978-3-319-32859-1_52

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-32858-4

  • Online ISBN: 978-3-319-32859-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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