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Ibero-American Conference on Artificial Intelligence

IBERAMIA 2014: Advances in Artificial Intelligence -- IBERAMIA 2014 pp 405–417Cite as

Parallel MOEA/D-ACO on GPU

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8864))

Abstract

This paper describes the idea of MOEA/D-ACO (Multiobjective Evolutionary Algorithm based on Decomposition and Ant Colony Optimization) and proposes a Graphics Processing Unit (GPU) implementation of MOEA/D-ACO using NVIDIA CUDA (Compute Unified Device Architecture) in order to improve the execution time. ACO is well-suited to GPU implementation, and both the solution construction and pheromone update phase are implemented using a data parallel approach. The parallel implementation is applied on the Multiobjective 0-1 Knapsack Problem and the Multiobjective Traveling Salesman Problem and reports speedups up to 19x and 11x respectively from the sequential counterpart with similar quality results. Moreover, the results show that the size of test instances, the number of objectives and the number of subproblems directly affect the speedup.

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Author information

Authors and Affiliations

  1. DInf, Federal University of Parana, CP: 19081, Curitiba, 19031-970, Brazil

    Murilo Zangari de Souza & Aurora Trinidad Ramirez Pozo

Authors
  1. Murilo Zangari de Souza
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  2. Aurora Trinidad Ramirez Pozo
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Corresponding author

Correspondence to Murilo Zangari de Souza .

Editor information

Editors and Affiliations

  1. Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil

    Ana L.C. Bazzan

  2. Pontifica Universidad Católica (PUC), Santiago de Chile, Chile

    Karim Pichara

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© 2014 Springer International Publishing Switzerland

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de Souza, M.Z., Pozo, A.T.R. (2014). Parallel MOEA/D-ACO on GPU. In: Bazzan, A., Pichara, K. (eds) Advances in Artificial Intelligence -- IBERAMIA 2014. IBERAMIA 2014. Lecture Notes in Computer Science(), vol 8864. Springer, Cham. https://doi.org/10.1007/978-3-319-12027-0_33

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  • DOI: https://doi.org/10.1007/978-3-319-12027-0_33

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-12026-3

  • Online ISBN: 978-3-319-12027-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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