International Journal of Computational Intelligence Systems

Volume 9, Issue 1, January 2016, Pages 80 - 90

An improved fruit fly optimization algorithm based on selecting evolutionary direction intelligently *

Authors
Wu Lei, wuleiupc@163.com
College of mechanical and electronic engineering, China University of Petroleum, No. 66, Changjiang West Road, Huangdao District, Qingdao, Shangdong Province, China
Xiao Wensheng
College of mechanical and electronic engineering, China University of Petroleum, No. 66, Changjiang West Road, Huangdao District, Qingdao, Shangdong Province, China
Zhang Liang
College of mechanical and electronic engineering, China University of Petroleum, No. 66, Changjiang West Road, Huangdao District, Qingdao, Shangdong Province, China
Liu Qi
College of mechanical and electronic engineering, China University of Petroleum, No. 66, Changjiang West Road, Huangdao District, Qingdao, Shangdong Province, China
Wang Jingli
College of mechanical and electronic engineering, China University of Petroleum, No. 66, Changjiang West Road, Huangdao District, Qingdao, Shangdong Province, China
*Corresponding author: Wu Lei, Email address: wuleiupc@163.com
Corresponding Author
Received 19 July 2015, Accepted 1 December 2015, Available Online 1 January 2016.
DOI
10.1080/18756891.2016.1144155How to use a DOI?
Keywords
fruit fly optimization algorithm; intelligent selection; the best search direction; benchmark functions; experimental simulation
Abstract

As a novel global optimization algorithm, the fruit fly optimization algorithm FOA has been successfully applied in a variety of mathematic and engineering fields. For the purpose of accelerating the convergence speed and overcoming the shortcomings of FOA, an improved fruit fly optimization called SEDI-FOA was proposed in this paper. In the proposed SEDI-FOA, more fruit flies would fly in the search direction that was best for finding the optimal solution, or at least in a direction close to the optimal direction. Experiments were conducted on a set of 12 benchmark functions, and the results showed that SEDI-FOA performed better than other several improved FOA and frequently-used intelligence algorithms, especially in the areas of accelerating convergence and global search ability and efficiency.

Copyright
© 2016. the authors. Co-published by Atlantis Press and Taylor & Francis
Open Access
This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).

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Journal
International Journal of Computational Intelligence Systems
Volume-Issue
9 - 1
Pages
80 - 90
Publication Date
2016/01/01
ISSN (Online)
1875-6883
ISSN (Print)
1875-6891
DOI
10.1080/18756891.2016.1144155How to use a DOI?
Copyright
© 2016. the authors. Co-published by Atlantis Press and Taylor & Francis
Open Access
This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).

Cite this article

TY  - JOUR
AU  - Wu Lei
AU  - Xiao Wensheng
AU  - Zhang Liang
AU  - Liu Qi
AU  - Wang Jingli
PY  - 2016
DA  - 2016/01/01
TI  - An improved fruit fly optimization algorithm based on selecting evolutionary direction intelligently *
JO  - International Journal of Computational Intelligence Systems
SP  - 80
EP  - 90
VL  - 9
IS  - 1
SN  - 1875-6883
UR  - https://doi.org/10.1080/18756891.2016.1144155
DO  - 10.1080/18756891.2016.1144155
ID  - Lei2016
ER  -