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Memetic Algorithms for Business Analytics and Data Science: A Brief Survey

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Abstract

This chapter reviews applications of Memetic Algorithms in the areas of business analytics and data science. This approach originates from the need to address optimization problems that involve combinatorial search processes. Some of these problems were from the area of operations research, management science, artificial intelligence and machine learning. The methodology has developed considerably since its beginnings and now is being applied to a large number of problem domains. This work gives a historical timeline of events to explain the current developments and, as a survey, gives emphasis to the large number of applications in business and consumer analytics that were published between January 2014 and May 2018.

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Acknowledgements

Pablo Moscato acknowledges previous support from the Australian Research Council Future Fellowship FT120100060 and Australian Research Council Discovery Projects DP120102576 and DP140104183. The authors thank Mohammad Nazmul Haque for his help during the preparation of this manuscript.

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  1. School of Electrical Engineering and Computing, The University of Newcastle, Callaghan, NSW, Australia

    Pablo Moscato & Luke Mathieson

  2. School of Software, University of Technology Sydney, Ultimo, NSW, Australia

    Luke Mathieson

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  1. School of Electrical Engineering and Computing, The University of Newcastle, Callaghan, NSW, Australia

    Pablo Moscato

  2. School of Electrical Engineering and Computing, The University of Newcastle, Callaghan, NSW, Australia

    Natalie Jane de Vries

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Moscato, P., Mathieson, L. (2019). Memetic Algorithms for Business Analytics and Data Science: A Brief Survey. In: Moscato, P., de Vries, N. (eds) Business and Consumer Analytics: New Ideas. Springer, Cham. https://doi.org/10.1007/978-3-030-06222-4_13

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  • DOI: https://doi.org/10.1007/978-3-030-06222-4_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-06221-7

  • Online ISBN: 978-3-030-06222-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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