Maximizing Vector Distances for Purpose of Searching—A Study of Differential Evolution Suitability

  • Martin Kolařík
  • Roman Jašek
  • Zuzana Komínková Oplatková
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 303)

Abstract

This paper explores suitability of using of differential evolution for maximizing of weighted distances of vectors in a set of vectors. Increase in vector distances simplifies searching for the best matching vector what is a common task in many areas (for instance in biometric identification of people). Maximizing of weighted distances itself is complex and nonlinear problem. The differential evolution is efficient enough and helps in decreasing of the computational complexity space compared to enumerative methods where all possible combinations are calculated. To find out, if differential evolution can help with the problem, model experiments were introduced and executed. Experiments showed that differential evolution is able to resolve the problem.

Keywords

optimization differential evolution distance metric nonlinear 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Martin Kolařík
    • 1
  • Roman Jašek
    • 1
  • Zuzana Komínková Oplatková
    • 1
  1. 1.Faculty of Applied InformaticsTomas Bata University in ZlinZlínCzech Republic

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