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The Role of Artificial Neural Networks in Evolutionary Optimisation: A Review

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Advances in Evolutionary and Deterministic Methods for Design, Optimization and Control in Engineering and Sciences

Part of the book series: Computational Methods in Applied Sciences ((COMPUTMETHODS,volume 36))

Abstract

This paper reviews the combination of Artificial Neural Networks (ANN) and Evolutionary Optimisation (EO) to solve challenging problems for the academia and the industry. Both methodologies has been mixed in several ways in the last decade with more or less degree of success, but most of the contributions can be classified into the two following groups: the use of EO techniques for optimizing the learning of ANN (EOANN) and the developing of ANNs to increase the efficiency of EO processes (ANNEO). The number of contributions shows that the combination of both methodologies is nowadays a mature field but some new trends and the advances in computer science permits to affirm that there is still room for noticeable improvements.

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  1. División de Computación Evolutiva y Aplicaciones (CEANI), Instituto Universitario de Sistemas Inteligentes y Aplicaciones Numéricas en Ingeniería (SIANI), Universidad de Las Palmas de Gran Canaria, Islas Canarias, Spain

    M. Maarouf, A. Sosa, B. Galván, D. Greiner, G. Winter, M. Mendez & R. Aguasca

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  1. SIANI, Universidad de Las Palmas de Gran Canaria, Las Palmas de Gran Canaria, Spain

    David Greiner

  2. SIANI, Universidad de Las Palmas de Gran Canaria, Las Palmas de Gran Canaria, Spain

    Blas Galván

  3. CIMNE, University of Jyväskylä, Jyväskylä, Finland, and Universitat Politècnica de Catalunya, Barcelona, Spain, Barcelona, Spain

    Jacques Périaux

  4. RWTH Aachen University, Aachen, Germany

    Nicolas Gauger

  5. National Technical University of Athens, Athens, Greece

    Kyriakos Giannakoglou

  6. SIANI, Universidad de Las Palmas de Gran Canaria, Las Palmas de Gran Canaria, Spain

    Gabriel Winter

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Maarouf, M. et al. (2015). The Role of Artificial Neural Networks in Evolutionary Optimisation: A Review. In: Greiner, D., Galván, B., Périaux, J., Gauger, N., Giannakoglou, K., Winter, G. (eds) Advances in Evolutionary and Deterministic Methods for Design, Optimization and Control in Engineering and Sciences. Computational Methods in Applied Sciences, vol 36. Springer, Cham. https://doi.org/10.1007/978-3-319-11541-2_4

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