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International Conference on Multimedia and Network Information System

MISSI 2018: Multimedia and Network Information Systems pp 512–521Cite as

Visual Analysis of Differential Evolution Algorithms

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Part of the Advances in Intelligent Systems and Computing book series (AISC,volume 833)

Abstract

In this article a web tool which contributes to the visual analysis of the Differential Evolution (DE) algorithms is presented. The tool provides a graphic interface with 8 views that allows understanding the underlying process of the algorithm. The tool has a library which extracts data from DE algorithms and its main feature is that the functions of the library can be embedded in the code of any DE algorithm to be analyzed. To validate the tool, three DE algorithms: DE/Rand/1/bin, DE/best/1/bin, and JADE and three test functions: Sphere, Rosenbrock, and Rastrigin have been used, which produced a total of 234 different tests, all of them performed successfully. The tool can allow to experts to analyze algorithms, particularly DE algorithms, and it can contribute to improve such algorithms or in generating new strategies that can emerge from the analysis of the extracted information.

Keywords

  • Differential evolution algorithms
  • Algorithm analysis
  • Web tool

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  • DOI: 10.1007/978-3-319-98678-4_51
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References

  1. Hart, E., Ross, P.: GAVEL - a new tool for genetic algorithm visualization. IEEE Trans. Evol. Comput. 5(2), 335–348 (2001)

    CrossRef  Google Scholar 

  2. Wu, H.-C., Sun, C.-T., Lee, S.-S.: Visualization of evolutionary computation processes: from the perspective of population. In: Proceedings of the Fifth World Congress on Intelligent Control and Automation, pp. 2077–2081. IEEE Xplore, Hangzhou (2004)

    Google Scholar 

  3. Kerren, A., Egger, T.: EAVis: a visualization tool for evolutionary algorithms. In: IEEE Symposium on Visual Languages and Human-Centric Computing, pp. 299–301. IEEE Xplore, Texas (2005)

    Google Scholar 

  4. Lutton, E., Fekete, J.D.: Visual analytics and experimental analysis of evolutionary algorithms. INRIA Rapport de recherche 7605 (2011)

    Google Scholar 

  5. Bullock, S., Bedau, M.A.: Exploring the dynamics of adaptation with evolutionary activity plots. Artif. Life 12(2), 193–197 (2006)

    CrossRef  Google Scholar 

  6. Pohlheim, H.: Visualization of evolutionary algorithms - set of standard techniques and multidimensional visualization. In: Proceedings of the 1st Annual Conference on Genetic and Evolutionary Computation, vol. 1, pp. 533–540. Morgan Kaufmann Publishers Inc., San California (1999)

    Google Scholar 

  7. Lotif, M.: Visualizing the population of meta-heuristics during the optimization process using self-organizing maps. In: IEEE Congress on Evolutionary Computation, pp. 312–319. IEEE Xplore, Beijing (2014)

    Google Scholar 

  8. Mach, M., Zetakova, Z.: Visualising genetic algorithms: a way through the labyrinth of search space. In: Sincak, P., Vascak, J., Kvasnicak, V., Pospichal, J. (eds.) Intelligent Technologies-Theory and Applications, pp. 279–285. IOS Press, Amsterdam (2002)

    Google Scholar 

  9. The R Foundation: Comprehensive R Archive Network. The R Project for Statistical Computing (2015). http://www.r-project.org/index.html

  10. Institut de Radioprotection et de Sûreté Nucléaire, WebGL in Shiny. http://trestletechgithub.io/shinyRGL/. Accessed 2013

  11. Pérez, J., Alvarado, L., Almanza, N., Mexicano, A., Zavala, C.: A graphical visualization tool for analyzing the behavior of metaheuristic algorithms. In: Proceedings of ICITSEM, Dubai, UAE, pp. 120–124 (2014)

    Google Scholar 

  12. Suganthan, P.N., Hansen, N., Liang, J., Deb, K., Chen, Y.P., Auger, A., Tiwari, S.: Problem Definitions and Evaluation Criteria for the CEC 2005 Special Session on Real-Parameter Optimization. Nanyang Technological University, Singapore (2005)

    Google Scholar 

  13. Price, K.V., Storn, R.M., Lampinen, J.A.: Differential Evolution: A Practical Approach to Global Optimization. Springer, New York (2005)

    MATH  Google Scholar 

  14. Zhang, J., Sanderson, A.C.: JADE: adaptive differential evolution with optional external archive. IEEE Trans. Evol. Comput. 13(5), 945–958 (2009)

    CrossRef  Google Scholar 

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Acknowledgements

The project is supported by a research grant No. DSA/103.5/16/10473 awarded by PRODEP and by Autonomous University of Ciudad Juarez. Title - Detection of Cardiac Arrhythmia Patterns through Adaptive Analysis.

Author information

Authors and Affiliations

  1. Instituto Tecnológico de Cd., Victoria, Mexico

    A. Mexicano-Santoyo, A. Abrego, M. A. Jiménez & R. Zúñiga-Treviño

  2. Institute of Engineering and Technology, Universidad Autónoma de Ciudad Juárez, Partido Romero, 32310, Ciudad Juarez, Mexico

    R. Rodríguez-Jorge & Edgar A. Martínez-Garcia

  3. Universidad Autónoma de Tamaulipas Cd., Victoria, Mexico

    A. Abrego

Authors
  1. A. Mexicano-Santoyo
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  2. R. Rodríguez-Jorge
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  3. A. Abrego
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  4. M. A. Jiménez
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  5. R. Zúñiga-Treviño
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  6. Edgar A. Martínez-Garcia
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Corresponding author

Correspondence to R. Rodríguez-Jorge .

Editor information

Editors and Affiliations

  1. Faculty of Computer Science and Management, Wrocław University of Science and Technology, Wrocław, Poland

    Kazimierz Choroś

  2. Faculty of Computer Science and Management, Wrocław University of Science and Technology, Wrocław, Poland

    Marek Kopel

  3. Faculty of Computer Science and Management, Wrocław University of Science and Technology, Wrocław, Poland

    Elżbieta Kukla

  4. Faculty of Computer Science and Management, Wrocław University of Science and Technology, Wrocław, Poland

    Andrzej Siemiński

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Mexicano-Santoyo, A., Rodríguez-Jorge, R., Abrego, A., Jiménez, M.A., Zúñiga-Treviño, R., Martínez-Garcia, E.A. (2019). Visual Analysis of Differential Evolution Algorithms. In: Choroś, K., Kopel, M., Kukla, E., Siemiński, A. (eds) Multimedia and Network Information Systems. MISSI 2018. Advances in Intelligent Systems and Computing, vol 833. Springer, Cham. https://doi.org/10.1007/978-3-319-98678-4_51

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