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Parallelism, hybridism and coevolution in a multi‐level ABC‐GA approach for the protein structure prediction problem
Author(s) -
Benitez César Manuel Vargas,
Parpinelli Rafael Stubs,
Lopes Heitor Silvério
Publication year - 2011
Publication title -
concurrency and computation: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.309
H-Index - 67
eISSN - 1532-0634
pISSN - 1532-0626
DOI - 10.1002/cpe.1857
Subject(s) - coevolution , benchmark (surveying) , parallelism (grammar) , computer science , genetic algorithm , parallel computing , machine learning , biology , geodesy , geography , paleontology
SUMMARY This paper reports the hybridization of the artificial bee colony (ABC) and a genetic algorithm (GA), in a hierarchical topology, a step ahead of a previous work. We used this parallel approach for solving the protein structure prediction problem using the three‐dimensional hydrophobic‐polar model with side‐chains (3DHP‐SC). The proposed method was run in a parallel processing environment (Beowulf cluster), and several aspects of the modeling and implementation are presented and discussed. The performance of the hybrid‐hierarchical ABC‐GA approach was compared with a hybrid‐hierarchical ABC‐only approach for four benchmark instances. Results show that the hybridization of the ABC with the GA improves the quality of solutions caused by the coevolution effect between them and their search behavior. Copyright © 2011 John Wiley & Sons, Ltd.