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Artificial Intelligence Review

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30.05.2016

Plant intelligence based metaheuristic optimization algorithms

verfasst von: Sinem Akyol, Bilal Alatas

Erschienen in: Artificial Intelligence Review | Ausgabe 4/2017

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Abstract

Classical optimization algorithms are insufficient in large scale combinatorial problems and in nonlinear problems. Hence, metaheuristic optimization algorithms have been proposed. General purpose metaheuristic methods are evaluated in nine different groups: biology-based, physics-based, social-based, music-based, chemical-based, sport-based, mathematics-based, swarm-based, and hybrid methods which are combinations of these. Studies on plants in recent years have showed that plants exhibit intelligent behaviors. Accordingly, it is thought that plants have nervous system. In this work, all of the algorithms and applications about plant intelligence have been firstly collected and searched. Information is given about plant intelligence algorithms such as Flower Pollination Algorithm, Invasive Weed Optimization, Paddy Field Algorithm, Root Mass Optimization Algorithm, Artificial Plant Optimization Algorithm, Sapling Growing up Algorithm, Photosynthetic Algorithm, Plant Growth Optimization, Root Growth Algorithm, Strawberry Algorithm as Plant Propagation Algorithm, Runner Root Algorithm, Path Planning Algorithm, and Rooted Tree Optimization.

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Titel: Plant intelligence based metaheuristic optimization algorithms
verfasst von: Sinem Akyol
Bilal Alatas
Publikationsdatum: 30.05.2016
Verlag: Springer Netherlands
Erschienen in: Artificial Intelligence Review / Ausgabe 4/2017
Print ISSN: 0269-2821
Elektronische ISSN: 1573-7462
DOI: https://doi.org/10.1007/s10462-016-9486-6

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