Simulation of a new hybrid particle swarm optimization algorithm

Ping Luo; Peihong Ni; Lihai Yao; Siu Lau Ho; Guangzheng Ni; Haixia Xia

Simulation of a new hybrid particle swarm optimization algorithm

Ping Luo, Peihong Ni, Lihai Yao, Siu Lau Ho, Guangzheng Ni, Haixia Xia

The Hong Kong Polytechnic University

Research output: Journal article publication › Journal article › Academic research › peer-review

7 Citations (Scopus)

Abstract

In this paper, a new hybrid Particle Swarm Optimization algorithm is introduced which makes use of the characteristics of Simulated Annealing method, and the crossover and mutation operations of Genetic Algorithms. Simulation results demonstrate that the proposed algorithm observes faster convergent rate for a certain class of optimal problems.

Original language	English
Pages (from-to)	705-710
Number of pages	6
Journal	International Journal of Applied Electromagnetics and Mechanics
Volume	25
Issue number	1-4
Publication status	Published - 4 Jun 2007

Keywords

Crossover
Mutation
Optimization
Particle swarm optimization

ASJC Scopus subject areas

Electronic, Optical and Magnetic Materials
Condensed Matter Physics
Mechanics of Materials
Mechanical Engineering
Electrical and Electronic Engineering

Cite this

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title = "Simulation of a new hybrid particle swarm optimization algorithm",

abstract = "In this paper, a new hybrid Particle Swarm Optimization algorithm is introduced which makes use of the characteristics of Simulated Annealing method, and the crossover and mutation operations of Genetic Algorithms. Simulation results demonstrate that the proposed algorithm observes faster convergent rate for a certain class of optimal problems.",

keywords = "Crossover, Mutation, Optimization, Particle swarm optimization",

author = "Ping Luo and Peihong Ni and Lihai Yao and Ho, {Siu Lau} and Guangzheng Ni and Haixia Xia",

year = "2007",

month = jun,

day = "4",

language = "English",

volume = "25",

pages = "705--710",

journal = "International Journal of Applied Electromagnetics and Mechanics",

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TY - JOUR

T1 - Simulation of a new hybrid particle swarm optimization algorithm

AU - Luo, Ping

AU - Ni, Peihong

AU - Yao, Lihai

AU - Ho, Siu Lau

AU - Ni, Guangzheng

AU - Xia, Haixia

PY - 2007/6/4

Y1 - 2007/6/4

N2 - In this paper, a new hybrid Particle Swarm Optimization algorithm is introduced which makes use of the characteristics of Simulated Annealing method, and the crossover and mutation operations of Genetic Algorithms. Simulation results demonstrate that the proposed algorithm observes faster convergent rate for a certain class of optimal problems.

AB - In this paper, a new hybrid Particle Swarm Optimization algorithm is introduced which makes use of the characteristics of Simulated Annealing method, and the crossover and mutation operations of Genetic Algorithms. Simulation results demonstrate that the proposed algorithm observes faster convergent rate for a certain class of optimal problems.

KW - Crossover

KW - Mutation

KW - Optimization

KW - Particle swarm optimization

UR - http://www.scopus.com/inward/record.url?scp=34249731503&partnerID=8YFLogxK

M3 - Journal article

SN - 1383-5416

VL - 25

SP - 705

EP - 710

JO - International Journal of Applied Electromagnetics and Mechanics

JF - International Journal of Applied Electromagnetics and Mechanics

IS - 1-4

ER -

Simulation of a new hybrid particle swarm optimization algorithm

Abstract

Keywords

ASJC Scopus subject areas

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