NDLI: Particle Swarm Optimization with Group Decision Making

Content Provider	IEEE Xplore Digital Library
Author	Liang Wang Zhihua Cui Jianchao Zeng
Copyright Year	2009
Abstract	The particle swarm optimization (PSO) is a stochastic optimization algorithm imitating animal behavior, which shows a bad performance when optimizing the multimodal and high dimensional functions. Each particle uses own experience and other’s to make decision, it is easy to trap into premature convergence, but group decision making with all the individuals to make decisions uses various experiences and viewpoints to get better plan for avoiding conformity. A new formal particle swarm optimization is advanced basing on group decision(GDPSO)¿it takes each particle as an individual decision-maker and uses the basic information of particle such as the position of individual history and fitness value to decide a new position, then using the position replaces the global best position (P_gj). So the space of searching is expanded and the population diversity is increased through the new improved algorithm, it can improve the convergence speed and the capacity of global searching, the premature convergence is avoided to some degree.
Starting Page	388
Ending Page	393
File Size	275209
Page Count	6
File Format	PDF
ISBN	9780769537450
DOI	10.1109/HIS.2009.82
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-08-12
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	group decision making Decision making Laboratories Optimization methods Cognition particle swarm optimization Particle swarm optimization Convergence premature convergence Neural networks Iterative algorithms Computational intelligence Random number generation
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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