Forest Optimization Algorithm

被引：160

作者：

Ghaemi, Manizheh ^{[1
]}

Feizi-Derakhshi, Mohammad-Reza ^{[2
]}

机构：

[1] Univ Tabriz, Dept Comp Sci, Tabriz, Iran

[2] Univ Tabriz, Fac Elect & Comp Engn, Tabriz, Iran

来源：

EXPERT SYSTEMS WITH APPLICATIONS | 2014年 / 41卷 / 15期

关键词：

Forest Optimization Algorithm (FOA); Evolutionary algorithms; Nonlinear optimization; Data mining; Feature weighting; DIFFERENTIAL EVOLUTION; DISPERSAL;

D O I：

10.1016/j.eswa.2014.05.009

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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. (C) 2014 Elsevier Ltd. All rights reserved.

引用

页码：6676 / 6687

页数：12

共 22 条

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