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Is Differential Evolution Sensitive to Pseudo Random Number Generator Quality? – An Investigation

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Intelligent Systems Technologies and Applications

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 384))

Abstract

This paper intends to investigate the sensitivity of Differential Evolution (DE) algorithm towards Pseudo Random Number Generator (PRNG) quality. Towards this, the impact of six PRNGs on the performance quality of 14 DE variants in solving nineteen 10-Dimensional benchmark functions has been studied. The results suggest that DE algorithm is insensitive to the quality of PRNG used.

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Author information

Authors and Affiliations

  1. Amrita Vishwa Vidyapeetham, Coimbatore, India

    Lekshmi Rajashekharan & C. Shunmuga Velayutham

Authors
  1. Lekshmi Rajashekharan
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  2. C. Shunmuga Velayutham
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Corresponding author

Correspondence to C. Shunmuga Velayutham .

Editor information

Editors and Affiliations

  1. Dipartimento di Ingegneria dell’ Informazione (DINFO) , Universita degli Studi di Firenze, Firenze, Italy

    Stefano Berretti

  2. School of CS/IT, Indian Institute of Information Tech. and Management – Kerala (IIITM-K), Trivandrum, Kerala, India

    Sabu M. Thampi

  3. Indian Institute of Management Rohtak, Rohtak, Haryana, India

    Praveen Ranjan Srivastava

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© 2016 Springer International Publishing Switzerland

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Rajashekharan, L., Shunmuga Velayutham, C. (2016). Is Differential Evolution Sensitive to Pseudo Random Number Generator Quality? – An Investigation. In: Berretti, S., Thampi, S., Srivastava, P. (eds) Intelligent Systems Technologies and Applications. Advances in Intelligent Systems and Computing, vol 384. Springer, Cham. https://doi.org/10.1007/978-3-319-23036-8_26

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  • DOI: https://doi.org/10.1007/978-3-319-23036-8_26

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-23035-1

  • Online ISBN: 978-3-319-23036-8

  • eBook Packages: EngineeringEngineering (R0)

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