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Proceedings of the Fifth International Conference on Innovations in Bio-Inspired Computing and Applications IBICA 2014

Volume 303 of the series Advances in Intelligent Systems and Computing pp 419-428

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

  • Martin KolaříkAffiliated withFaculty of Applied Informatics, Tomas Bata University in Zlin Email author 
  • , Roman JašekAffiliated withFaculty of Applied Informatics, Tomas Bata University in Zlin
  • , Zuzana Komínková OplatkováAffiliated withFaculty of Applied Informatics, Tomas Bata University in Zlin

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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