NDLI: Particle swarm optimization with opposition-based disturbance

Content Provider	IEEE Xplore Digital Library
Author	Yuancheng Chi Guobiao Cai
Copyright Year	2010
Description	Author affiliation: School of Astronautics, Beijing University of Aeronautics and Astronautics, China (Yuancheng Chi; Guobiao Cai)
Abstract	Particle swarm optimization (PSO) often traps in the local optimal solutions. In this paper, an opposition-based disturbance procedure was introduced into a basic PSO, which was abbreviated as PSOOD. For this proposed algorithm, opposition-based disturbance was implemented according to the probability when the personal best position was updated for each particle. Such procedure not only avoids the missing of cognition component in the velocity update equation, but also increases the population diversity. Numerical tests on three benchmark functions were conducted to compare the algorithm performances. The results show that PSOOD is able to escape from the local optimal solutions efficiently when solving complex optimization problems, which enhances the global search ability obviously while guaranteeing the convergence.
Starting Page	223
Ending Page	226
File Size	1049123
Page Count	4
File Format	PDF
ISBN	9781424451920
ISSN	19483422
DOI	10.1109/CAR.2010.5456563
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-03-06
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Additive noise disturbance Transmitting antennas Rayleigh channels Particle swarm optimization Robotics and automation global optimization prticle swarm optimization (PSO) Transmitters Receiving antennas Cost function MIMO Labeling opposition-based learning (OBL)
Content Type	Text
Resource Type	Article

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