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Evaluating the Multiple Offspring Sampling framework on complex continuous optimization functions

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Abstract

In this contribution we present a study on the combination of Differential Evolution and the IPOP-CMA-ES algorithms. The hybrid algorithm has been constructed by using the Multiple Offspring Sampling framework, which allows the seamless combination of multiple metaheuristics in a dynamic algorithm capable of adjusting the participation of each of the composing algorithms according to their current performance. In this study we analyze the existing synergies, if any, emerging from the combination of the two algorithms. For this purpose, the COCO suite used in BBOB 2009 and 2010 Workshops has been used. The experimental results on the noiseless testbed show a robust behavior of the algorithm and a good scalability as the dimensionality increases. In the noisy testbed, the algorithm shows a good performance on functions with moderate to severe noise.

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Notes

  1. The complete 120 results in the noiseless testbed can be accessed in the following URL: http://laurel.datsi.fi.upm.es/research.

  2. The complete 150 results in the noisy testbed can be accessed in the following URL: http://laurel.datsi.fi.upm.es/research.

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Acknowledgments

This work was financed by the Spanish Ministry of Science (TIN2010-21289-C02-02) and supported by the Cajal Blue Brain Project. The authors thankfully acknowledge the computer resources, technical expertise and assistance provided by the Centro de Supercomputación y Visualización de Madrid (CeSViMa) and the Spanish Supercomputing Network. A. LaTorre gratefully acknowledges the support of the Spanish Ministry of Science and Innovation (MICINN) for its funding throughout the Juan de la Cierva program.

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Authors and Affiliations

  1. Department of Computer Systems Architecture and Technology, Facultad de Informática, Universidad Politécnica de Madrid, Boadilla del Monte, 28660 , Madrid, Spain

    Antonio LaTorre, Santiago Muelas & José-María Peña

  2. Instituto Cajal, Consejo Superior de Investigaciones Científicas (CSIC), Madrid, Spain

    Antonio LaTorre

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  1. Antonio LaTorre
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  2. Santiago Muelas
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  3. José-María Peña
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Correspondence to Antonio LaTorre.

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LaTorre, A., Muelas, S. & Peña, JM. Evaluating the Multiple Offspring Sampling framework on complex continuous optimization functions. Memetic Comp. 5, 295–309 (2013). https://doi.org/10.1007/s12293-013-0120-8

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  • DOI: https://doi.org/10.1007/s12293-013-0120-8

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