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Please use this identifier to cite or link to this item: http://repository.iitr.ac.in/handle/123456789/19020
Title: A new hybrid self organizing migrating genetic algorithm for function optimization
Authors: Deep, K.
Dipti
Published in: Proceedings of 2007 IEEE Congress on Evolutionary Computation, CEC 2007
Abstract: This paper presents a new Self Organizing Migrating Genetic Algorithm (SOMGA) for function optimization, which is inspired by the features of Self Organizing Migrating Algorithm (SOMA). The uniqueness of this algorithm is that it is hybridization of binary coded GA and real coded SOMA. We compare its performance to Simple Genetic Algorithm (GA) and SOMA on 25 test functions. This algorithm is shown to be far more robust than GA and SOMA, providing fast convergence across a broad range of parameter settings. © 2007 IEEE.
Citation: Proceedings of 2007 IEEE Congress on Evolutionary Computation, CEC 2007, (2007), 2796- 2803
URI: https://doi.org/10.1109/CEC.2007.4424825
http://repository.iitr.ac.in/handle/123456789/19020
Issue Date: 2007
Keywords: Function optimization
Self Organizing Migrating Genetic Algorithm (SOMGA)
Test functions
Computational efficiency
Convergence of numerical methods
Function evaluation
Optimization
Self organizing maps
Genetic algorithms
ISBN: 1424413400; 9781424413409
Author Scopus IDs: 8561208900
23767790900
Author Affiliations: Deep, K., Department of Mathematics, Indian Institute of Technology, Roorkee, Uttrakhand, India
Dipti, Department of Mathematics, Indian Institute of Technology, Roorkee, Uttrakhand, India
Corresponding Author: Deep, K.; Department of Mathematics, Indian Institute of Technology, Roorkee, Uttrakhand, India; email: kusumfma@iitr.ernet.in
Appears in Collections:Conference Publications [MA]

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