NDLI: The Distance-Guided Particle Swarm Optimizer with Dynamic Mutation

Content Provider	IEEE Xplore Digital Library
Author	Chunhe Song Hai Zhao Wei Cai Haohua Zhang Ming Zhao Wei Gao Xuanjie Ning Xudong Han Peng Zhu Jie Gao Tianyu Qi Hongyan Gong
Copyright Year	2007
Abstract	This paper presents a distance-guided particle swarm optimizer with dynamic mutation (PSODM). Two characteristics are proposed in the PSODM: distance-guided and dynamic mutation. The goal of these characteristics is to overcome premature convergence of the swarm and accelerating the convergence velocity. With distance-guided operation, some particles too intense can be separated, while with dynamic mutation operation, the particles mutated can find a better position more easily by effectively using the foregone experience. The PSODM is compared to other four types of improved PSO, and the experimental results show that the PSODM performances better on a six-function test suite with different dimensions.
Starting Page	342
Ending Page	345
File Size	96940
Page Count	4
File Format	PDF
ISBN	9780769529941
DOI	10.1109/IIH-MSP.2007.292
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-11-26
Publisher Place	Taiwan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Performance evaluation Computational modeling Genetic mutations Evolutionary computation Performance loss Acceleration Particle swarm optimization Equations Convergence Testing
Content Type	Text
Resource Type	Article

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The Distance-Guided Particle Swarm Optimizer with Dynamic Mutation