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A Study of the Performance of \(\text {Self-}{\star }\) Memetic Algorithms on Heterogeneous Ephemeral Environments

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Parallel Problem Solving from Nature – PPSN XIV (PPSN 2016)

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Abstract

We consider the deployment of island-based memetic algorithms (MAs) endowed with \(\text {self-}{\star }\) properties on unstable computational environments composed of a collection of computing nodes whose availability fluctuates. In this context, these properties refer to the ability of the MA to work autonomously in order to optimize its performance and to react to the instability of computational resources. The main focus of this work is analyzing the performance of such MAs when the underlying computational substrate is not only volatile but also heterogeneous in terms of the computational power of each of its constituent nodes. We use for this purpose a simulated environment subject to different volatility rates, whose topology is modeled as scale-free networks and whose computing power is distributed among nodes following different distributions. We observe that in general computational homogeneity is preferable in scenarios with low instability; in case of high instability, MAs without self-scaling and self-healing perform better when the computational power follows a power law, but performance seems to be less sensitive to the distribution when these \(\text {self-}{\star }\) properties are used.

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Acknowledgements

We acknowledge support from Spanish MinEco and FEDER under project EphemeCH (TIN2014-56494-C4-1-P), from Junta de Andalucía under project DNEMESIS (P10-TIC-6083), and from Universidad de Málaga, Campus de Excelencia Internacional Andalucía Tech.

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Authors and Affiliations

  1. Dept. Lenguajes y Ciencias de la Computación, Universidad de Málaga, ETSI Informática, Campus de Teatinos, 29071, Málaga, Spain

    Rafael Nogueras & Carlos Cotta

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  1. Rafael Nogueras
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  2. Carlos Cotta
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Correspondence to Carlos Cotta .

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Editors and Affiliations

  1. University of Manchester, Manchester, United Kingdom

    Julia Handl

  2. Edinburgh Napier University, Edinburgh, United Kingdom

    Emma Hart

  3. Aston University, Birmingham, United Kingdom

    Peter R. Lewis

  4. University of Manchester, Manchester, United Kingdom

    Manuel López-Ibáñez

  5. University of Stirling, Stirling, United Kingdom

    Gabriela Ochoa

  6. Edinburgh Napier University, Edinburgh, United Kingdom

    Ben Paechter

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Nogueras, R., Cotta, C. (2016). A Study of the Performance of \(\text {Self-}{\star }\) Memetic Algorithms on Heterogeneous Ephemeral Environments. In: Handl, J., Hart, E., Lewis, P., López-Ibáñez, M., Ochoa, G., Paechter, B. (eds) Parallel Problem Solving from Nature – PPSN XIV. PPSN 2016. Lecture Notes in Computer Science(), vol 9921. Springer, Cham. https://doi.org/10.1007/978-3-319-45823-6_9

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  • DOI: https://doi.org/10.1007/978-3-319-45823-6_9

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