Description of simple genetic algorithm modifications using Generalized Nets

Roeva, O; Shannon, A; Pencheva, T

Description of simple genetic algorithm modifications using Generalized Nets

Roeva, O Shannon, A

Pencheva, T

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Publication Type:: Conference Proceeding
Citation:: IS'2012 - 2012 6th IEEE International Conference Intelligent Systems, Proceedings, 2012, pp. 178 - 183
Issue Date:: 2012-11-28

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Field	Value	Language
dc.contributor.author	Roeva, O	en_US
dc.contributor.author	Shannon, A https://orcid.org/0000-0003-0116-0666	en_US
dc.contributor.author	Pencheva, T	en_US
dc.date.issued	2012-11-28	en_US
dc.identifier.citation	IS'2012 - 2012 6th IEEE International Conference Intelligent Systems, Proceedings, 2012, pp. 178 - 183	en_US
dc.identifier.isbn	9781467327824	en_US
dc.identifier.uri	http://hdl.handle.net/10453/22965
dc.description.abstract	The apparatus of Generalized Nets (GN) is applied here to describe different kinds of genetic algorithms (GA). Failure of conventional optimization methods to lead to a satisfied solution in parameter identification of non-linear and time-dependent parameters provokes an idea some stochastic algorithms to be applied. As such genetic algorithms (GA), as a promising metaheuristic technique, are widely used. Different modifications of simple genetic algorithms (SGA) have been investigated and successfully applied to parameter identification of fermentation processes aiming to improve the model accuracy and the algorithm convergence time. Altogether six modifications of SGA have been proposed with a different sequence of implementation of basic genetic operators selection, crossover and mutation. In the present GN model the user is allowed to choose the sequence of execution of main GA operators, thus resulting in one of the six considered here modifications of SGA. © 2012 IEEE.	en_US
dc.relation.ispartof	IS'2012 - 2012 6th IEEE International Conference Intelligent Systems, Proceedings	en_US
dc.relation.isbasedon	10.1109/IS.2012.6335212	en_US
dc.title	Description of simple genetic algorithm modifications using Generalized Nets	en_US
dc.type	Conference Proceeding
utslib.for	0802 Computation Theory and Mathematics	en_US
dc.location.activity	Sofia, Bulgaria	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

The apparatus of Generalized Nets (GN) is applied here to describe different kinds of genetic algorithms (GA). Failure of conventional optimization methods to lead to a satisfied solution in parameter identification of non-linear and time-dependent parameters provokes an idea some stochastic algorithms to be applied. As such genetic algorithms (GA), as a promising metaheuristic technique, are widely used. Different modifications of simple genetic algorithms (SGA) have been investigated and successfully applied to parameter identification of fermentation processes aiming to improve the model accuracy and the algorithm convergence time. Altogether six modifications of SGA have been proposed with a different sequence of implementation of basic genetic operators selection, crossover and mutation. In the present GN model the user is allowed to choose the sequence of execution of main GA operators, thus resulting in one of the six considered here modifications of SGA. © 2012 IEEE.

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http://hdl.handle.net/10453/22965