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The Journal of Supercomputing

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09-01-2020

Robust parallel hybrid artificial bee colony algorithms for the multi-dimensional numerical optimization

Authors: Tansel Dokeroglu, Selen Pehlivan, Bilgin Avenoglu

Published in: The Journal of Supercomputing | Issue 9/2020

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Abstract

This study proposes a set of new robust parallel hybrid metaheuristic algorithms based on artificial bee colony (ABC) and teaching learning-based optimization (TLBO) for the multi-dimensional numerical problems. The best practices of ABC and TLBO are implemented to provide robust algorithms on a distributed memory computation environment using MPI libraries. Island parallel versions of the proposed hybrid algorithm are observed to obtain much better results than those of sequential versions. Parallel pseudorandom number generators are used to provide diverse solution candidates to prevent stagnation into local optima. The performances of the proposed hybrid algorithms are compared with eight different metaheuristics algorithms of particle swarm optimization, differential evolution variants, ABC variants and evolutionary algorithm. The empirical results show that the new hybrid parallel algorithms are scalable and the best performing algorithms when compared to the state-of-the-art metaheuristics.

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Title: Robust parallel hybrid artificial bee colony algorithms for the multi-dimensional numerical optimization
Authors: Tansel Dokeroglu
Selen Pehlivan
Bilgin Avenoglu
Publication date: 09-01-2020
Publisher: Springer US
Published in: The Journal of Supercomputing / Issue 9/2020
Print ISSN: 0920-8542
Electronic ISSN: 1573-0484
DOI: https://doi.org/10.1007/s11227-019-03127-7

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