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Artificial Intelligence Review

Erschienen in:

19.01.2019

From ants to whales: metaheuristics for all tastes

verfasst von: Fernando Fausto, Adolfo Reyna-Orta, Erik Cuevas, Ángel G. Andrade, Marco Perez-Cisneros

Erschienen in: Artificial Intelligence Review | Ausgabe 1/2020

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Abstract

Nature-inspired metaheuristics comprise a compelling family of optimization techniques. These algorithms are designed with the idea of emulating some kind natural phenomena (such as the theory of evolution, the collective behavior of groups of animals, the laws of physics or the behavior and lifestyle of human beings) and applying them to solve complex problems. Nature-inspired methods have taken the area of mathematical optimization by storm. Only in the last few years, literature related to the development of this kind of techniques and their applications has experienced an unprecedented increase, with hundreds of new papers being published every single year. In this paper, we analyze some of the most popular nature-inspired optimization methods currently reported on the literature, while also discussing their applications for solving real-world problems and their impact on the current literature. Furthermore, we open discussion on several research gaps and areas of opportunity that are yet to be explored within this promising area of science.

Vorheriger Artikel Robust multi-criteria decision making methodology for real life logistics center location problem

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Titel: From ants to whales: metaheuristics for all tastes
verfasst von: Fernando Fausto
Adolfo Reyna-Orta
Erik Cuevas
Ángel G. Andrade
Marco Perez-Cisneros
Publikationsdatum: 19.01.2019
Verlag: Springer Netherlands
Erschienen in: Artificial Intelligence Review / Ausgabe 1/2020
Print ISSN: 0269-2821
Elektronische ISSN: 1573-7462
DOI: https://doi.org/10.1007/s10462-018-09676-2

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