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2008 10th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing
An Adaptive Particle Swarm Optimizer Using Balanced Explorative and Exploitative Behaviors
Timisoara, Romania
September 26-September 29
ISBN: 978-0-7695-3523-4
ASCII Text
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Sayan Ghosh, Debarati Kundu, Kaushik Suresh, Swagatam Das, Ajith Abraham, "An Adaptive Particle Swarm Optimizer Using Balanced Explorative and Exploitative Behaviors," Symbolic and Numeric Algorithms for Scientific Computing, International Symposium on, pp. 543-550, 2008 10th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, 2008.
 
 
BibTex
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@article{ 10.1109/SYNASC.2008.20,
author = {Sayan Ghosh and Debarati Kundu and Kaushik Suresh and Swagatam Das and Ajith Abraham},
title = {An Adaptive Particle Swarm Optimizer Using Balanced Explorative and Exploitative Behaviors},
journal ={Symbolic and Numeric Algorithms for Scientific Computing, International Symposium on},
volume = {0},
year = {2008},
isbn = {978-0-7695-3523-4},
pages = {543-550},
doi = {http://doi.ieeecomputersociety.org/10.1109/SYNASC.2008.20},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - Symbolic and Numeric Algorithms for Scientific Computing, International Symposium on
TI - An Adaptive Particle Swarm Optimizer Using Balanced Explorative and Exploitative Behaviors
SN - 978-0-7695-3523-4
SP543
EP550
A1 - Sayan Ghosh,
A1 - Debarati Kundu,
A1 - Kaushik Suresh,
A1 - Swagatam Das,
A1 - Ajith Abraham,
PY - 2008
KW - particle swarm optimization
KW - adaptive inertia
VL - 0
JA - Symbolic and Numeric Algorithms for Scientific Computing, International Symposium on
ER -
 
Particle Swarm Optimization (PSO) has recently emerged as a nature inspired algorithm for real parameter optimization. This article describes a method for improving the final accuracy and the convergence speed of PSO by adding a new coefficient to the position updating equation and modulating the inertia weight. This work also mathematically analyzes the effect of this modification on the PSO algorithm. The new algorithm has been shown to be statistically significantly better than four recent variants of PSO on a six-functions test-suite.
Index Terms:
particle swarm optimization, adaptive inertia
Citation:
Sayan Ghosh, Debarati Kundu, Kaushik Suresh, Swagatam Das, Ajith Abraham, "An Adaptive Particle Swarm Optimizer Using Balanced Explorative and Exploitative Behaviors," synasc, pp.543-550, 2008 10th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, 2008
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