An investigation into mutation operators for Particle Swarm Optimization

Paul S. Andrews

An investigation into mutation operators for Particle Swarm Optimization

Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

The Particle Swarm Optimization (PSO) technique can be augmented with an additional mutation operator that helps prevent premature convergence on local optima. In this paper, different mutation operators for PSO are empirically investigated and compared. A review of previous mutation approaches is given and key factors concerning how mutation operators can be applied to PSO are identified. A PSO algorithm incorporating different mutation operators is applied to both mathematical and constrained optimization problems. Results shown that the addition of a mutation operator to PSO can enhance optimisation performance and insight is gained into how to design mutation operators dependent on the nature of the problem being optimized.

Original language	English
Title of host publication	2006 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-6
Place of Publication	NEW YORK
Publisher	IEEE
Pages	1029-1036
Number of pages	8
ISBN (Print)	978-0-7803-9487-2
Publication status	Published - 2006
Event	IEEE Congress on Evolutionary Computation - Vancouver Duration: 16 Jul 2006 → 21 Jul 2006

Conference

Conference	IEEE Congress on Evolutionary Computation
City	Vancouver
Period	16/07/06 → 21/07/06

Cite this

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title = "An investigation into mutation operators for Particle Swarm Optimization",

abstract = "The Particle Swarm Optimization (PSO) technique can be augmented with an additional mutation operator that helps prevent premature convergence on local optima. In this paper, different mutation operators for PSO are empirically investigated and compared. A review of previous mutation approaches is given and key factors concerning how mutation operators can be applied to PSO are identified. A PSO algorithm incorporating different mutation operators is applied to both mathematical and constrained optimization problems. Results shown that the addition of a mutation operator to PSO can enhance optimisation performance and insight is gained into how to design mutation operators dependent on the nature of the problem being optimized.",

author = "Andrews, {Paul S.}",

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booktitle = "2006 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-6",

publisher = "IEEE",

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note = "IEEE Congress on Evolutionary Computation ; Conference date: 16-07-2006 Through 21-07-2006",

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AU - Andrews, Paul S.

PY - 2006

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N2 - The Particle Swarm Optimization (PSO) technique can be augmented with an additional mutation operator that helps prevent premature convergence on local optima. In this paper, different mutation operators for PSO are empirically investigated and compared. A review of previous mutation approaches is given and key factors concerning how mutation operators can be applied to PSO are identified. A PSO algorithm incorporating different mutation operators is applied to both mathematical and constrained optimization problems. Results shown that the addition of a mutation operator to PSO can enhance optimisation performance and insight is gained into how to design mutation operators dependent on the nature of the problem being optimized.

AB - The Particle Swarm Optimization (PSO) technique can be augmented with an additional mutation operator that helps prevent premature convergence on local optima. In this paper, different mutation operators for PSO are empirically investigated and compared. A review of previous mutation approaches is given and key factors concerning how mutation operators can be applied to PSO are identified. A PSO algorithm incorporating different mutation operators is applied to both mathematical and constrained optimization problems. Results shown that the addition of a mutation operator to PSO can enhance optimisation performance and insight is gained into how to design mutation operators dependent on the nature of the problem being optimized.

M3 - Conference contribution

SN - 978-0-7803-9487-2

SP - 1029

EP - 1036

BT - 2006 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-6

PB - IEEE

CY - NEW YORK

T2 - IEEE Congress on Evolutionary Computation

Y2 - 16 July 2006 through 21 July 2006

ER -