International Journal of Computational Intelligence Systems

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Volume 5, Issue 3, June 2012, Pages 483 - 493

An Optimization Algorithm Based on Binary Difference and Gravitational Evolution

Authors
Junli Li, Yang Lou, Yuhui Shi
Corresponding Author
Junli Li
Received 6 December 2010, Accepted 14 February 2012, Available Online 1 June 2012.
DOI
10.1080/18756891.2012.696912How to use a DOI?
Keywords
Optimization, Binary Difference, Differential Evolution, Gravitation
Abstract

Universal gravitation is a natural phenomenon. Inspired by Newton's universal gravitation model and based on binary differences strategy, we propose an algorithm for global optimization problems, which is called the binary difference gravitational evolution (BDGE) algorithm. BDGE is a population-based algorithm, and the population is composed of particles. Each particle is treated as a virtual object with two attributes of position and quality. Some of the best objects in the population compose the reference-group and the rest objects compose the floating-group. The BDGE algorithm could find the global optimum solutions through two critical operations: the self-update of reference-group and the interactive-update process between the reference-group and floating-group utilizing the gravitational evolution method. The parameters of BDGE are set by a trial-and-error process and the BDGE is proved that it can converge to the global optimal solution with probability 1. Benchmark functions are used to evaluate the performance of BDGE and to compare it with classic Differential Evolution. The simulation results illustrate the encouraging performance of the BDGE algorithm with regards to computing speed and accuracy.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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<Previous Article In Issue
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Journal
International Journal of Computational Intelligence Systems
Volume-Issue
5 - 3
Pages
483 - 493
Publication Date
2012/06/01
ISSN (Online)
1875-6883
ISSN (Print)
1875-6891
DOI
10.1080/18756891.2012.696912How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

risenwbib
TY  - JOUR
AU  - Junli Li
AU  - Yang Lou
AU  - Yuhui Shi
PY  - 2012
DA  - 2012/06/01
TI  - An Optimization Algorithm Based on Binary Difference and Gravitational Evolution
JO  - International Journal of Computational Intelligence Systems
SP  - 483
EP  - 493
VL  - 5
IS  - 3
SN  - 1875-6883
UR  - https://doi.org/10.1080/18756891.2012.696912
DO  - 10.1080/18756891.2012.696912
ID  - Li2012
ER  -