On the improved performances of the particle swarm optimization algorithms with adaptive parameters, cross-over operators and root mean square (RMS) variants for computing optimal control of a class of hybrid systems

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On the improved performances of the particle swarm optimization algorithms with adaptive parameters, cross-over operators and root mean square (RMS) variants for computing optimal control of a class of hybrid systems

This paper deals with the concept of including the popular genetic algorithm operator, cross-over and root mean square (RMS) variants into particle swarm optimization (PSO) algorithm to make the convergence faster. Two different PSO algorithms are considered in this paper: the first one is the conve...

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Bibliographic Details
Main Authors:	Arumugam, M. Senthil, Rao, M.V.C.
Format:	Article
Published:	ELSEVIER SCIENCE BV 2008
Subjects:	T Technology (General) QA75.5-76.95 Electronic computers. Computer science
Online Access:	http://shdl.mmu.edu.my/2779/

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