Forest Optimization Algorithm(FOA)

Forest Optimization Algorithm - Matlab Code

https://github.com/cominsys/FOA

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FOA

Forest Optimization Algorithm - Matlab Code

Doi: https://doi.org/10.1016/j.eswa.2014.05.009

URL: http://www.sciencedirect.com/science/article/pii/S0957417414002899

Article's Abstract:

In this article, a new evolutionary algorithm, Forest Optimization Algorithm (FOA), suitable for continuous nonlinear optimization problems has been proposed. It is inspired by few trees in the forests which can survive for several decades, while other trees could live for a limited period. In FOA, seeding procedure of the trees is simulated so that, some seeds fall just under the trees, while others are distributed in wide areas by natural procedures and the animals that feed on the seeds or fruits. Application of the proposed algorithm on some benchmark functions demonstrated its good capability in comparison with Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). Also we tested the performance of FOA on feature weighting as a real optimization problem and the results of the experiments showed the good performance of FOA in some data sets from the UCI repository.

Cite:

@article{GHAEMI20146676,
title = {Forest Optimization Algorithm},
journal = {Expert Systems with Applications},
volume = {41},
number = {15},
pages = {6676-6687},
year = {2014},
issn = {0957-4174},
doi = {https://doi.org/10.1016/j.eswa.2014.05.009},
url = {https://www.sciencedirect.com/science/article/pii/S0957417414002899},
author = {Manizheh Ghaemi and Mohammad-Reza Feizi-Derakhshi},
keywords = {Forest Optimization Algorithm (FOA), Evolutionary algorithms, Nonlinear optimization, Data mining, Feature weighting}
}

Cite As

Ghaemi, Manizheh, and Mohammad-Reza Feizi-Derakhshi. “Forest Optimization Algorithm.” Expert Systems with Applications, vol. 41, no. 15, Elsevier BV, Nov. 2014, pp. 6676–87, doi:10.1016/j.eswa.2014.05.009.

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General Information

MATLAB Release Compatibility

  • Compatible with any release

Platform Compatibility

  • Windows
  • macOS
  • Linux
Version Published Release Notes Action
1.0

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