Binary Particle Swarm Optimization with Bit Change Mutation

Sangwook LEE; Haesun PARK; Moongu JEON

doi:10.1093/ietfec/e90-a.10.2253

Binary Particle Swarm Optimization with Bit Change Mutation

Sangwook LEE, Haesun PARK, Moongu JEON

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Particle swarm optimization (PSO), inspired by social psychology principles and evolutionary computations, has been successfully applied to a wide range of continuous optimization problems. However, research on discrete problems has been done not much even though discrete binary version of PSO (BPSO) was introduced by Kennedy and Eberhart in 1997. In this paper, we propose a modified BPSO algorithm, which escapes from a local optimum by employing a bit change mutation. The proposed algorithm was tested on De jong's suite and its results show that BPSO with the proposed mutation outperforms the original BPSO.

Publication: IEICE TRANSACTIONS on Fundamentals Vol.E90-A No.10 pp.2253-2256

Publication Date: 2007/10/01

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Online ISSN: 1745-1337

DOI: 10.1093/ietfec/e90-a.10.2253

Type of Manuscript: Special Section LETTER (Special Section on Nonlinear Theory and its Applications)

Category: Optimization

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Sangwook LEE, Haesun PARK, Moongu JEON, "Binary Particle Swarm Optimization with Bit Change Mutation" in IEICE TRANSACTIONS on Fundamentals, vol. E90-A, no. 10, pp. 2253-2256, October 2007, doi: 10.1093/ietfec/e90-a.10.2253.
Abstract: Particle swarm optimization (PSO), inspired by social psychology principles and evolutionary computations, has been successfully applied to a wide range of continuous optimization problems. However, research on discrete problems has been done not much even though discrete binary version of PSO (BPSO) was introduced by Kennedy and Eberhart in 1997. In this paper, we propose a modified BPSO algorithm, which escapes from a local optimum by employing a bit change mutation. The proposed algorithm was tested on De jong's suite and its results show that BPSO with the proposed mutation outperforms the original BPSO.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1093/ietfec/e90-a.10.2253/_p

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@ARTICLE{e90-a_10_2253,
author={Sangwook LEE, Haesun PARK, Moongu JEON, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Binary Particle Swarm Optimization with Bit Change Mutation},
year={2007},
volume={E90-A},
number={10},
pages={2253-2256},
abstract={Particle swarm optimization (PSO), inspired by social psychology principles and evolutionary computations, has been successfully applied to a wide range of continuous optimization problems. However, research on discrete problems has been done not much even though discrete binary version of PSO (BPSO) was introduced by Kennedy and Eberhart in 1997. In this paper, we propose a modified BPSO algorithm, which escapes from a local optimum by employing a bit change mutation. The proposed algorithm was tested on De jong's suite and its results show that BPSO with the proposed mutation outperforms the original BPSO.},
keywords={},
doi={10.1093/ietfec/e90-a.10.2253},
ISSN={1745-1337},
month={October},}

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TY - JOUR
TI - Binary Particle Swarm Optimization with Bit Change Mutation
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 2253
EP - 2256
AU - Sangwook LEE
AU - Haesun PARK
AU - Moongu JEON
PY - 2007
DO - 10.1093/ietfec/e90-a.10.2253
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E90-A
IS - 10
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - October 2007
AB - Particle swarm optimization (PSO), inspired by social psychology principles and evolutionary computations, has been successfully applied to a wide range of continuous optimization problems. However, research on discrete problems has been done not much even though discrete binary version of PSO (BPSO) was introduced by Kennedy and Eberhart in 1997. In this paper, we propose a modified BPSO algorithm, which escapes from a local optimum by employing a bit change mutation. The proposed algorithm was tested on De jong's suite and its results show that BPSO with the proposed mutation outperforms the original BPSO.
ER -