Study on the compression-expansion coefficient in drift particle swarm optimization

Wei Fang; Jun Sun; Xiaojun Wu; Wenbo Xu; Vasile Palade

doi:10.1109/CEC.2012.6256621

Study on the compression-expansion coefficient in drift particle swarm optimization

Wei Fang, Jun Sun, Xiaojun Wu, Wenbo Xu, Vasile Palade

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding › peer-review

2 Citations (Scopus)

Abstract

This paper introduces a variant of particle swarm optimization algorithm called the drift particle swarm optimization (DPSO), which is inspired by the free electron model in an external electric field at finite temperature. As the compression-expansion coefficient in DPSO is an important parameter which can greatly influence the performance of the algorithm, three types of control strategies are proposed to control this parameter. The performance of these strategies on the DPSO is comprehensively evaluated on eight benchmark functions. From the experimental results and statistical tests, guidelines about selecting the control method for the compression-expansion coefficient are given.

Original language	English
Title of host publication	2012 IEEE Congress on Evolutionary Computation, CEC 2012
Publisher	IEEE
Number of pages	6
ISBN (Print)	9781467315098
DOIs	https://doi.org/10.1109/CEC.2012.6256621
Publication status	Published - 2012
Externally published	Yes
Event	2012 IEEE Congress on Evolutionary Computation, CEC 2012 - Brisbane, QLD, Australia Duration: 10 Jun 2012 → 15 Jun 2012

Conference

Conference	2012 IEEE Congress on Evolutionary Computation, CEC 2012
Country/Territory	Australia
City	Brisbane, QLD
Period	10/06/12 → 15/06/12

Keywords

compression-expansion coefficient
drift motion
particle swarm optimization
thermal motion

ASJC Scopus subject areas

Computational Theory and Mathematics
Theoretical Computer Science

Access to Document

10.1109/CEC.2012.6256621

Cite this

@inproceedings{2437a40df0144b8d82d07c401c285288,

title = "Study on the compression-expansion coefficient in drift particle swarm optimization",

abstract = "This paper introduces a variant of particle swarm optimization algorithm called the drift particle swarm optimization (DPSO), which is inspired by the free electron model in an external electric field at finite temperature. As the compression-expansion coefficient in DPSO is an important parameter which can greatly influence the performance of the algorithm, three types of control strategies are proposed to control this parameter. The performance of these strategies on the DPSO is comprehensively evaluated on eight benchmark functions. From the experimental results and statistical tests, guidelines about selecting the control method for the compression-expansion coefficient are given.",

keywords = "compression-expansion coefficient, drift motion, particle swarm optimization, thermal motion",

author = "Wei Fang and Jun Sun and Xiaojun Wu and Wenbo Xu and Vasile Palade",

year = "2012",

doi = "10.1109/CEC.2012.6256621",

language = "English",

isbn = "9781467315098",

booktitle = "2012 IEEE Congress on Evolutionary Computation, CEC 2012",

publisher = "IEEE",

address = "United States",

note = "2012 IEEE Congress on Evolutionary Computation, CEC 2012 ; Conference date: 10-06-2012 Through 15-06-2012",

}

TY - GEN

T1 - Study on the compression-expansion coefficient in drift particle swarm optimization

AU - Fang, Wei

AU - Sun, Jun

AU - Wu, Xiaojun

AU - Xu, Wenbo

AU - Palade, Vasile

PY - 2012

Y1 - 2012

N2 - This paper introduces a variant of particle swarm optimization algorithm called the drift particle swarm optimization (DPSO), which is inspired by the free electron model in an external electric field at finite temperature. As the compression-expansion coefficient in DPSO is an important parameter which can greatly influence the performance of the algorithm, three types of control strategies are proposed to control this parameter. The performance of these strategies on the DPSO is comprehensively evaluated on eight benchmark functions. From the experimental results and statistical tests, guidelines about selecting the control method for the compression-expansion coefficient are given.

AB - This paper introduces a variant of particle swarm optimization algorithm called the drift particle swarm optimization (DPSO), which is inspired by the free electron model in an external electric field at finite temperature. As the compression-expansion coefficient in DPSO is an important parameter which can greatly influence the performance of the algorithm, three types of control strategies are proposed to control this parameter. The performance of these strategies on the DPSO is comprehensively evaluated on eight benchmark functions. From the experimental results and statistical tests, guidelines about selecting the control method for the compression-expansion coefficient are given.

KW - compression-expansion coefficient

KW - drift motion

KW - particle swarm optimization

KW - thermal motion

U2 - 10.1109/CEC.2012.6256621

DO - 10.1109/CEC.2012.6256621

M3 - Conference proceeding

AN - SCOPUS:84866869467

SN - 9781467315098

BT - 2012 IEEE Congress on Evolutionary Computation, CEC 2012

PB - IEEE

T2 - 2012 IEEE Congress on Evolutionary Computation, CEC 2012

Y2 - 10 June 2012 through 15 June 2012

ER -

Study on the compression-expansion coefficient in drift particle swarm optimization

Abstract

Conference

Keywords

ASJC Scopus subject areas

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Cite this