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Distance Measures for Permutations in Combinatorial Efficient Global Optimization

  • Conference paper
Parallel Problem Solving from Nature – PPSN XIII (PPSN 2014)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8672))

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Abstract

For expensive black-box optimization problems, surrogate-model based approaches like Efficient Global Optimization are frequently used in continuous optimization. Their main advantage is the reduction of function evaluations by exploiting cheaper, data-driven models of the actual target function. The utilization of such methods in combinatorial or mixed search spaces is less common. Efficient Global Optimization and related methods were recently extended to such spaces, by replacing continuous distance (or similarity) measures with measures suited for the respective problem representations.

This article investigates a large set of distance measures for their applicability to various permutation problems. The main purpose is to identify, how a distance measure can be chosen, either a-priori or online. In detail, we show that the choice of distance measure can be integrated into the Maximum Likelihood Estimation process of the underlying Kriging model. This approach has robust, good performance, thus providing a very nice tool towards selection of a distance measure.

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Authors and Affiliations

  1. Faculty for Computer and Engineering Sciences, Cologne University of Applied Sciences, 51643, Gummersbach, Germany

    Martin Zaefferer, Jörg Stork & Thomas Bartz-Beielstein

Authors
  1. Martin Zaefferer
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  2. Jörg Stork
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  3. Thomas Bartz-Beielstein
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Editor information

Editors and Affiliations

  1. Faculty of Computer and Engineering Sciences, Cologne University of Applied Sciences, Steinmüllerallee 1, 51643, Gummersbach, Germany

    Thomas Bartz-Beielstein

  2. Warwick Business School, University of Warwick, CV8 2SY, Coventry, UK

    Jürgen Branke

  3. Department of Intelligent Systems, JožefStefan Institute, Jamova cesta 39, 1000, Ljubljana, Slovenia

    Bogdan Filipič

  4. Department of Computer Science and Creative Technologies, University of the West of England, BS16 1QY, Bristol, UK

    Jim Smith

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© 2014 Springer International Publishing Switzerland

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Zaefferer, M., Stork, J., Bartz-Beielstein, T. (2014). Distance Measures for Permutations in Combinatorial Efficient Global Optimization. In: Bartz-Beielstein, T., Branke, J., Filipič, B., Smith, J. (eds) Parallel Problem Solving from Nature – PPSN XIII. PPSN 2014. Lecture Notes in Computer Science, vol 8672. Springer, Cham. https://doi.org/10.1007/978-3-319-10762-2_37

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  • DOI: https://doi.org/10.1007/978-3-319-10762-2_37

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-10761-5

  • Online ISBN: 978-3-319-10762-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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