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Data and Decision Sciences in Action pp 1–12Cite as

What Latin Hypercube Is Not

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

Abstract

Simulation methods play a key role in the modelling of theoretical or actual physical systems. Such models can approximate the behaviour of the real system and provide insights into its operation. Well-determined input parameters are of prime importance for obtaining reliable simulations due to their impact on the performance of the simulation design. Among various strategies for producing input parameter samples is Latin hypercube design (LHD). LHDs are generated by Latin hypercube sampling (LHS), a type of stratified sampling that can be applied to multiple variables. LHS has proven to be an efficient and popular method; however, it misses some important elements. While LHS focuses on the parameter space aspects, this paper highlights five more aspects which may greatly impact the efficiency of sampling. In this paper, we do not provide solutions but rather bring up unanswered questions which could be missed during strategy planning on model simulation.

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Notes

  1. 1.

    Note that randomness in probabilistic models cannot be included into the input to make the model deterministic, since the results represented as distributions rather than fixed values may reflect smoothness of the model which would be broken by fixing the seed to the random generator.

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Author information

Authors and Affiliations

  1. Defence Science and Technology (DST) Group, Department of Defence, Edinburgh, SA, 5111, Australia

    Oleg Mazonka

  2. Department of Electrical and Computer Engineering, New York University School of Engineering, Brooklyn, NY, 11201, USA

    Charalambos Konstantinou

Authors
  1. Oleg Mazonka
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  2. Charalambos Konstantinou
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Corresponding author

Correspondence to Oleg Mazonka .

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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© 2018 Springer International Publishing AG

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Mazonka, O., Konstantinou, C. (2018). What Latin Hypercube Is Not. 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_1

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  • DOI: https://doi.org/10.1007/978-3-319-55914-8_1

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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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