# 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:
```bib
@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}
}
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MATLAB 森林优化算法代码
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MATLAB 森林优化算法代码
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FOA-master.7z (13个子文件)
FOA-master
LocalSeeding.m 2KB
EvaluationSum.m 498B
EvaluationAckley.m 714B
PopulationLimiting.m 1KB
main.m 2KB
GlobalSeeding.m 1KB
EvaluationRastrigin.m 518B
InitializeForest.m 3KB
FOA.m 2KB
UpdateBestTree.m 1KB
README.md 2KB
EvaluationGriewangk.m 550B
EvaluationShubert.m 597B
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