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A Generalization of the Gravitational Search Algorithm

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Aggregation Functions in Theory and in Practice (AGOP 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 581))

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Abstract

In this work we propose a generalization of the gravitational search algorithm where the product in the expression of the gravitational attraction force is replaced by more general functions. We study some conditions which ensure convergence of our proposal and we show that we recover a wide class of aggregation functions to replace the product.

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References

  1. Ashlock, D.: Evolutionary Computation for Modeling and Optimization. Springer, New York (2005)

    MATH  Google Scholar 

  2. Bustince, H., Fernandez, J., Mesiar, R., Montero, J., Orduna, R.: Overlap functions. Nonlinear Anal. Theory Methods Appl. 72, 1488–1499 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  3. Ghorbani, F., Neamabadi-Pour, H.: On the convergence analysis of gravitational search algorithm. J. Adv. Comput. Res. 3(2), 45–51 (2012)

    Google Scholar 

  4. Grabisch, M., Marichal, J.-L., Mesiar, R., Pap, E.: Aggregation Functions. Cambridge University Press, Cambridge (2009)

    Book  MATH  Google Scholar 

  5. Haykin, S.: Neural Networks: A Comprehensive Foundation. Prentice Hall, Upper Saddle River (1999)

    MATH  Google Scholar 

  6. Lopez-Molina, C., Bustince, H., Fernandez, J., Couto, P., De Baets, B.: A gravitational approach to edge detection based on triangular norms. Pattern Recogn. 43, 3730–3741 (2010)

    Article  MATH  Google Scholar 

  7. Rashedi, E., Neamabadi-Pour, H., Sariazdi, S.: GSA: a gravitational search algorithm. Inf. Sci. 179(13), 2232–2248 (2009)

    Article  MATH  Google Scholar 

  8. Wright, W.E.: Gravitational clustering. Pattern Recogn. 9, 151–166 (1977)

    Article  Google Scholar 

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Acknowledgements

This work was supported by Spanish Research Project TIN-77356-P (AEI/FEDER, UE) and by projects APVV-14-0013 and VEGA-1/0420/15.

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Authors and Affiliations

  1. Public University of Navarra and Institute of Smart Cities, Campus Arrosadia s/n, 31006, Pamplona, Spain

    Humberto Bustince, Javier Fernandez, Mikel Sesma-Sara, Cedric Marco-Detchart & Javier Ruiz-Aranguren

  2. Slovak University of Technology, Radlinského 11, 813 68, Bratislava 1, Slovakia

    Maria Minárová

Authors
  1. Humberto Bustince
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  2. Maria Minárová
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  3. Javier Fernandez
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  4. Mikel Sesma-Sara
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  5. Cedric Marco-Detchart
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  6. Javier Ruiz-Aranguren
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Corresponding author

Correspondence to Humberto Bustince .

Editor information

Editors and Affiliations

  1. School of Informatics, University of Skövde, Skövde, Sweden

    Vicenç Torra

  2. Department of Mathematics and Descriptive Geometry, Slovak University of Technology, Bratislava, Slovakia

    Radko Mesiar

  3. KERMIT Research Unit Knowledge-based Systems, Ghent University, Ghent, Belgium

    Bernard De Baets

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Bustince, H., Minárová, M., Fernandez, J., Sesma-Sara, M., Marco-Detchart, C., Ruiz-Aranguren, J. (2018). A Generalization of the Gravitational Search Algorithm. In: Torra, V., Mesiar, R., Baets, B. (eds) Aggregation Functions in Theory and in Practice. AGOP 2017. Advances in Intelligent Systems and Computing, vol 581. Springer, Cham. https://doi.org/10.1007/978-3-319-59306-7_17

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  • DOI: https://doi.org/10.1007/978-3-319-59306-7_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-59305-0

  • Online ISBN: 978-3-319-59306-7

  • eBook Packages: EngineeringEngineering (R0)

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