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23rd International Conference on Soft Computing

MENDEL 2017: Recent Advances in Soft Computing pp 40–55Cite as

Enhanced Archive for SHADE

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 837))

Abstract

This research paper analyses an external archive of inferior solutions used in Success-History based Adaptive Differential Evolution (SHADE) and its variant with a linear decrease in population size L-SHADE. A novel implementation of an archive is proposed and compared to the original one on CEC2015 benchmark set of test functions for two distinctive dimensionality settings. The proposed archive implementation is referred to as Enhanced Archive (EA) and therefore two Differential Evolution (DE) variants are titled EA-SHADE and EA-L-SHADE. The results on CEC2015 benchmark set are analyzed and discussed.

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Acknowledgements

This work was supported by Grant Agency of the Czech Republic – GACR P103/15/06700S, further by the Ministry of Education, Youth and Sports of the Czech Republic within the National Sustainability Programme Project no. LO1303 (MSMT-7778/2014). Also by the European Regional Development Fund under the Project CEBIA-Tech no. CZ.1.05/2.1.00/03.0089 and by Internal Grant Agency of Tomas Bata University under the Projects no. IGA/CebiaTech/2017/004.

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Authors and Affiliations

  1. Faculty of Applied Informatics, Tomas Bata University in Zlin, T. G. Masaryka 5555, 760 01, Zlin, Czech Republic

    Adam Viktorin, Roman Senkerik, Michal Pluhacek & Tomas Kadavy

Authors
  1. Adam Viktorin
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  2. Roman Senkerik
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  3. Michal Pluhacek
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  4. Tomas Kadavy
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Corresponding author

Correspondence to Adam Viktorin .

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Editors and Affiliations

  1. Department of Applied Computer Science, Institute of Automation and Computer Science, Faculty of Mechanical Engineering, Brno University of Technology, Brno, Czech Republic

    Radek Matoušek

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Viktorin, A., Senkerik, R., Pluhacek, M., Kadavy, T. (2019). Enhanced Archive for SHADE. In: Matoušek, R. (eds) Recent Advances in Soft Computing . MENDEL 2017. Advances in Intelligent Systems and Computing, vol 837. Springer, Cham. https://doi.org/10.1007/978-3-319-97888-8_4

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