Abstract
Optimization is one of the most studied fields within the wider area of artificial intelligence. In the current literature, hundreds of works can be found focused on solving many diverse problems of this kind by resorting to a vast spectrum of solvers. In this context, Swarm Intelligence methods have gained significant popularity in the related community, maintaining a constant momentum in recent years, and having been applied to problems coming from a wide variety of real-world contexts. This chapter contributes to this line by presenting a systematic overview of Swarm Intelligence solvers applied to different branches of optimization problems. To do that, we have focused our attention on four of the most intensively studied application fields: transportation, energy, medicine, and industry. Apart from this systematic review, we also share in this paper our envisioned status of this area, by identifying the most interesting opportunities. These open challenges should stimulate the scientific efforts made by the community in the upcoming years.
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Acknowledgements
Eneko Osaba would like to thank the Basque Government for its funding support through the EMAITEK and ELKARTEK (Elkarbot project) programs.
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Osaba, E., Yang, XS. (2021). Applied Optimization and Swarm Intelligence: A Systematic Review and Prospect Opportunities. In: Osaba, E., Yang, XS. (eds) Applied Optimization and Swarm Intelligence. Springer Tracts in Nature-Inspired Computing. Springer, Singapore. https://doi.org/10.1007/978-981-16-0662-5_1
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