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Novel local improvement techniques in clustered memetic algorithm for protein structure prediction

conference contribution
posted on 2023-02-08, 00:17 authored by MK Islam, M Chetty, Manzur MurshedManzur Murshed
Evolutionary algorithms (EAs) often fail to find the global optimum due to genetic drift. As the protein structure prediction problem is multimodal having several global optima, EAs empowered with combined application of local and global search e.g., memetic algorithms, can be more effective. This paper introduces two novel local improvement techniques for the clustered memetic algorithm to incorporate both problem specific and search-space specific knowledge to find one of the optimum structures of a hydrophobic-polar protein sequence on lattice models. Experimental results show the superiority of the proposed techniques against existing EAs on benchmark sequences. © 2011 IEEE.

History

Pagination

1003-1011

Location

LA, New Orleans

Start date

2011-06-05

End date

2011-06-08

ISBN-13

9781424478347

Language

English

Title of proceedings

2011 IEEE Congress of Evolutionary Computation, CEC 2011

Event

IEEE Congress on Evolutionary Computation (CEC)

Publisher

IEEE

Series

IEEE Congress on Evolutionary Computation